Seismic comprehensive forecast based on modified project pursuit regression
Anxu Wu; Xiangdong Lin; Changsheng Jiang; Yongxian Zhang; Xiaodong Zhang; Mingxiao Li; Pingan Li
2009-01-01
In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression (PPR) is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation: to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.
Hongying Du
Full Text Available The epidermal growth factor receptor (EGFR protein tyrosine kinase (PTK is an important protein target for anti-tumor drug discovery. To identify potential EGFR inhibitors, we conducted a quantitative structure-activity relationship (QSAR study on the inhibitory activity of a series of quinazoline derivatives against EGFR tyrosine kinase. Two 2D-QSAR models were developed based on the best multi-linear regression (BMLR and grid-search assisted projection pursuit regression (GS-PPR methods. The results demonstrate that the inhibitory activity of quinazoline derivatives is strongly correlated with their polarizability, activation energy, mass distribution, connectivity, and branching information. Although the present investigation focused on EGFR, the approach provides a general avenue in the structure-based drug development of different protein receptor inhibitors.
On grey relation projection model based on projection pursuit
Wang Shuo; Yang Shanlin; Ma Xijun
2008-01-01
Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by u-sing projection pursuit model.The larger the projection value is,the better the model.Thus,according to the projection value,the best one can be chosen from the model aggregation.Because projection pursuit modeling based on accelera-ting genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.
李祚泳; 张正健; 余春雪
2012-01-01
Traditional projection pursuit regression represented with matrix, which is applied in water quality evaluation for multi-index, affects not only learning efficient of optimized parameter matrix element, but also optimal effects. The present work set the proper reference values and transformed forms for each index. Therefore, the different in the same grade standard values with different index could be weakened after the normal transformation, the normalized values of different indexes were e-quivalent to a certain normalized index. Therefore, it is only necessary to set up the models of NV-PPR (2) and NV-PPR(3) suited to 2 indexes and 3 indexes, respectively, for each normalized index values. Meanwhile, the optimization of the parameter matrix elements of model were iterated by monkey-king genetic algorithm. Furthermore, the multi-index NV-PPR model could be represented into the combinations of some NV-PPR (2) and (or) NV-PPR (3) models. The practicality of models was verified virtually. The results showed that the projection pursuit regression model of water quality evaluation based on normalized index transform exhibited the characteristics of simplicity in form, convenience during calculation, university as well as commonness.%传统的投影寻踪回归(PPR)的矩阵表示法用于水质评价,当指标较多时,不仅优化参数矩阵元的学习效率低,而且优化效果亦受到影响.若适当设置3类水体(地表水、地下水和富营养化水体)各指标的参照值及指标值的规范变换式,使不同指标的同级标准的规范值差异不大,从而可以认为用规范值表示的不同指标皆与某个规范指标“等效”.因此,只需构造并优化得出对各指标规范值都共同适用的2个指标变量的NV-PPR(2)和3个指标变量的NV-PPR(3)模型,对于指标变量较多的NV-PPR建模,只需将其分解为若干个NV-PPR(2)和(或)NV-PPR(3)的组合表示即可.对模型的实用性进行的效
王健; 张晓丽; 刘陶
2011-01-01
In view of the difficulty in nonlinear modeling for prediction of woven fabric permeability, a projection pursuit regression ( PPR) model for prediction of air permeability of woven fabrics was established using the structural parameters such as the total tightness, thickness, and weight per square meter and average float as factors affecting the prediction of woven fabric permeability. The fitted values of tested samples and the predicted values of trained samples were analyzed with the means and standard deviations of relative error as the indicators and were compared with the results of BP neural network and multiple linear regression model. The results showed that the PPR model fitting and prediction accuracy was better than those of BP neural network and multiple linear regression model. In the case of less trained samples, the PPR model still had relatively high prediction accuracy and good generalization ability, providing a novel approach to the prediction of woven fabric permeability.%针对机织物透气性预测中存在非线性建模困难的问题,选择机织物总紧度、厚度、面密度及平均浮长等结构参数作为机织物透气性预测的影响因素,建立机织物透气性预测的投影寻踪回归模型.对模型训练样本的拟合值及检验样本的预测值以相对误差的均值及标准差为指标进行分析,并与BP神经网络及多元线性回归模型进行对比.结果表明,投影寻踪回归模型的拟合及预测精度均优于BP神经网络及多元线性回归模型,且在训练样本较少的情况下,投影寻踪回归模型仍有较高的预测精度和较强的泛化能力,可为机织物透气性预测提供一种新的方法.
Asymptotic distributions in the projection pursuit based canonical correlation analysis
无
2010-01-01
In this paper, associations between two sets of random variables based on the projection pursuit (PP) method are studied. The asymptotic normal distributions of estimators of the PP based canonical correlations and weighting vectors are derived.
Approach to Weighted Geometric Evaluation Based on Projection Pursuit
Yang Shanlin; Wang Shuo; Gong Daning
2006-01-01
Weighted geometric evaluation approach based on Projection pursuit (PP) model is presented in this paper to optimize the choice of schemes. By using PP model, the multi-dimension evaluation index values of schemes can be synthesized into projection value with one dimension. The scheme with a bigger projection value is much better, so the schemes sample can be an optimized choice according to the projection value of each scheme. The modeling of PP based on accelerating genetic algorithm can predigest the realized process of projection pursuit technique, can overcome the shortcomings of large computation amount and the difficulty of computer programming in traditional projection pursuit methods, and can give a new method for application of projection pursuit technique to optimize choice of schemes by using weighted geometric evaluation. The analysis of an applied sample shows that applying PP model driven directly by samples data to optimize choice of schemes is both simple and feasible, that its projection values are relatively decentralized and profit decision-making, that its applicability and maneuverability are high. It can avoid the shortcoming of subjective weighing method, and its results are scientific and objective.
Brian M. Wood
2015-12-01
Full Text Available This article describes a software tool called “Pursuit” that is intended to be used for both research and teaching on the topic of optimal foraging theory. The tool provides a dynamic graphical and auditory interface in which users encounter different prey animals and then must decide whether to pursue or ignore the encountered prey. Based on the characteristics of the prey in the foraging environment and the decisions of the player, each user harvests a set of prey per round and achieves a corresponding foraging return rate. Administrators of Pursuit specify the environmental parameters that determine what prey users will encounter. All environmental parameters and user decisions are tracked and logged for analysis. We created this tool for laboratory experiments, but we believe Pursuit could also be an engaging and effective teaching tool, whereby students adopt the role of forager, and through such play, experience a simulated foraging context and learn about foraging theory. Pursuit is freely available and can run on any platform that supports Java, including Mac OS, Windows, and Linux.
Managing Performance Analysis with Dynamic Statistical Projection Pursuit
Vetter, J.S.; Reed, D.A.
2000-05-22
Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focusing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.
Projection Pursuit Through ϕ-Divergence Minimisation
Jacques Touboul
2010-06-01
Full Text Available In his 1985 article (“Projection pursuit”, Huber demonstrates the interest of his method to estimate a density from a data set in a simple given case. He considers the factorization of density through a Gaussian component and some residual density. Huber’s work is based on maximizing Kullback–Leibler divergence. Our proposal leads to a new algorithm. Furthermore, we will also consider the case when the density to be factorized is estimated from an i.i.d. sample. We will then propose a test for the factorization of the estimated density. Applications include a new test of fit pertaining to the elliptical copulas.
Procrustes rotation as a diagnostic tool for projection pursuit analysis.
Wentzell, Peter D; Hou, Siyuan; Silva, Carolina Santos; Wicks, Chelsi C; Pimentel, Maria Fernanda
2015-06-02
Projection pursuit (PP) is an effective exploratory data analysis tool because it optimizes the projection of high dimensional data using distributional characteristics rather than variance or distance metrics. The recent development of fast and simple PP algorithms based on minimization of kurtosis for clustering data has made this powerful tool more accessible, but under conditions where the sample-to-variable ratio is small, PP fails due to opportunistic overfitting of random correlations to limiting distributional targets. Therefore, some kind of variable compression or data regularization is required in these cases. However, this introduces an additional parameter whose optimization is manually time consuming and subject to bias. The present work describes the use of Procrustes analysis as diagnostic tool that can be used to evaluate the results of PP analysis in an efficient manner. Through Procrustes rotation, the similarity of different PP projections can be examined in an automated fashion with "Procrustes maps" to establish regions of stable projections as a function of the parameter to be optimized. The application of this diagnostic is demonstrated using principal components analysis to compress FTIR spectra from ink samples of ten different brands of pen, and also in conjunction with regularized PP for soybean disease classification. Copyright © 2015 Elsevier B.V. All rights reserved.
XU Zi-rong; ZHANG Yi-fei
2011-01-01
The paper studies on case-based reasoning of uncertain product attributes in configuration design of a product family. Interval numbers characterize uncertain product attributes. By interpolating a number of certain values randomly to replace interval numbers and making projection pursuit analysis on source cases and target cases of expanded numbers, we can get a projection value in the optimal projection direction. Based on projection value, we can construct a case retrieval model of projection pursuit that can handle coexisting certain and uncertain product attributes. The application examples of chainsaw configuration design show that case retrieval is highly sensitive to reliable results.
REPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit
Fischer, Daniel; Berro, Alain; Nordhausen, Klaus; Ruiz-Gazen, Anne
2016-01-01
The R-package REPPlab is designed to explore multivariate data sets using one-dimensional unsupervised projection pursuit. It is useful in practice as a preprocessing step to find clusters or as an outlier detection tool for multivariate numerical data. Except from the package tourr that implements smooth sequences of projection matrices and rggobi that provides an interface to a dynamic graphics package called GGobi, there is no implementation of exploratory projection pursuit tools availabl...
Coal Calorific Value Prediction Based on Projection Pursuit Principle
QI Minfang
2012-10-01
Full Text Available The calorific value of coal is an important factor for the economic operation of coal-fired power plant. However, calorific value is tremendous difference between the different coal, and even if coal is from the same mine. Restricted by the coal market, most of coal fired power plants can not burn the designed-coal by now in China. The properties of coal as received are changing so frequently that pulverized coal firing is always with the unexpected condition. Therefore, the researches on the prediction of calorific value of coal have a profound significance for the economic operation of power plants. Aiming at the problem of uncertainty of coal calorific value, establish a soft measurement model for calorific value of coal based on projection pursuit principle combined with genetic algorithm to optimize parameters, and support vector machine algorithm. It is shown by an example that the model has a stronger objectivity, effective and feasible for avoiding the disadvantage of the artificially decided weights of feature indexes. The model could provide a good guidance for the calculation of the coal calorific value and optimization operation of coal-fired power plants.
Benefit Evaluation Model of Small Watershed Control Based on Projection Pursuit
无
2001-01-01
A projection pursuit model is presented in this paper for comprehensive evaluation of benefits of small watershed control. By using the model ,small watershed control samples with many benefit evaluation indexes can be synthesized projective values with one dimension. The samples can be naturally evaluated according to the projective values. The parameters of the model is optimized by using real coding beased accelerating genetic aglrothm,which overcomes the shortcomings of large computation amount and difficulty of computer programming in traditional projection prusuit methods,and provides a new way for wide applications of projection pursuit technique to different evaluation problems in agricultural systems engineering.
Research on evaluating water resource resilience based on projection pursuit classification model
Liu, Dong; Zhao, Dan; Liang, Xu; Wu, Qiuchen
2016-03-01
Water is a fundamental natural resource while agriculture water guarantees the grain output, which shows that the utilization and management of water resource have a significant practical meaning. Regional agricultural water resource system features with unpredictable, self-organization, and non-linear which lays a certain difficulty on the evaluation of regional agriculture water resource resilience. The current research on water resource resilience remains to focus on qualitative analysis and the quantitative analysis is still in the primary stage, thus, according to the above issues, projection pursuit classification model is brought forward. With the help of artificial fish-swarm algorithm (AFSA), it optimizes the projection index function, seeks for the optimal projection direction, and improves AFSA with the application of self-adaptive artificial fish step and crowding factor. Taking Hongxinglong Administration of Heilongjiang as the research base and on the basis of improving AFSA, it established the evaluation of projection pursuit classification model to agriculture water resource system resilience besides the proceeding analysis of projection pursuit classification model on accelerating genetic algorithm. The research shows that the water resource resilience of Hongxinglong is the best than Raohe Farm, and the last 597 Farm. And the further analysis shows that the key driving factors influencing agricultural water resource resilience are precipitation and agriculture water consumption. The research result reveals the restoring situation of the local water resource system, providing foundation for agriculture water resource management.
Lin Wei; Tian Zheng; Wen Xianbin
2003-01-01
The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very difficult when little is known about apriori knowledge for multisource degraded factors. WDPPLN successfully resolves this problemby separately processing wavelet coefficients and scale coefficients. Parameters in WDPPLN,which are used to simulate degraded factors, are estimated via WDPPLN training, using scalecoefficients. Also, WDPPLN uses soft-threshold of wavelet shrinkage technique to suppress noisein three high frequency subbands. The new method is compared with the traditional methodsand the Projection Pursuit Learning Network (PPLN) method. Experimental results demonstratethat it is an effective method for unsupervised restoring degraded image.
PROJECTION-PURSUIT BASED PRINCIPAL COMPONENT ANALYSIS: A LARGE SAMPLE THEORY
Jian ZHANG
2006-01-01
The principal component analysis (PCA) is one of the most celebrated methods in analysing multivariate data. An effort of extending PCA is projection pursuit (PP), a more general class of dimension-reduction techniques. However, the application of this extended procedure is often hampered by its complexity in computation and by lack of some appropriate theory. In this paper, by use of the empirical processes we established a large sample theory for the robust PP estimators of the principal components and dispersion matrix.
Projection pursuit cluster model and its application in water quality assessment
WANG Shun-jiu; YANG Zhi-feng; DING Jing
2004-01-01
One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function ; (2) to find the right projection direction; (3) to calculate projection characteristic value of the sample , and (4) to draw comprehensive analysis on the basis of . On the other hand, the empirical formula of cutoff radius is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.
Goodness-of-Fit Tests For Elliptical and Independent Copulas through Projection Pursuit
Jacques Touboul
2011-04-01
Full Text Available Two goodness-of-fit tests for copulas are being investigated. The first one deals with the case of elliptical copulas and the second one deals with independent copulas. These tests result from the expansion of the projection pursuit methodology that we will introduce in the present article. This method enables us to determine on which axis system these copulas lie as well as the exact value of these very copulas in the basis formed by the axes previously determined irrespective of their value in their canonical basis. Simulations are also presented as well as an application to real datasets.
Souad Larabi Marie-Sainte
2017-01-01
Full Text Available This article consists of using biologically inspired algorithms in order to detect potentially interesting structures in large and multidimensional data sets. Data exploration and the detection of interesting structures are based on the use of Projection Pursuit that involves the definition and the optimization of an index associated with each direction or projection. The optimization of a projection index should provide a set of multiple optima that is expected to correspond to interesting graphical representations in low dimensional space. The implementation of the bio-inspired algorithms along with the projection pursuit develops a new software called EPP-Lab. Projection pursuit is widely used in different scientific domains (biology, pharmacy, bioinformatics, biometry, etc but not widely present in the well-known softwares. EPP-Lab is dedicated to recognize and visualize clusters and outlying observations on one dimension from high dimensional and multivariate data sets. It includes different statistical techniques for results analysis. It provides several features and gives the user the option to adjust the parameters of the selected bio-inspired methods or to use defaults values. EPP-Lab is a unique software for detection, visualization and analysis of non-linear structures. The performance of this tool has been validated by testing different real and simulated data sets.
Landscape ecological security assessment based on projection pursuit in Pearl River Delta.
Gao, Yang; Wu, Zhifeng; Lou, Quansheng; Huang, Huamei; Cheng, Jiong; Chen, Zhangli
2012-04-01
Regional landscape ecological security is an important issue for ecological security, and has a great influence on national security and social sustainable development. The Pearl River Delta (PRD) in southern China has experienced rapid economic development and intensive human activities in recent years. This study, based on landscape analysis, provides a method to discover the alteration of character among different landscape types and to understand the landscape ecological security status. Based on remotely sensed products of the Landsat 5 TM images in 1990 and the Landsat 7 ETM+ images in 2005, landscape classification maps of nine cities in the PRD were compiled by implementing Remote Sensing and Geographic Information System technology. Several indices, including aggregation, crush index, landscape shape index, Shannon's diversity index, landscape fragile index, and landscape security adjacent index, were applied to analyze spatial-temporal characteristics of landscape patterns in the PRD. A landscape ecological security index based on these outcomes was calculated by projection pursuit using genetic algorithm. The landscape ecological security of nine cities in the PRD was thus evaluated. The main results of this research are listed as follows: (1) from 1990 to 2005, the aggregation index, crush index, landscape shape index, and Shannon's diversity index of nine cities changed little in the PRD, while the landscape fragile index and landscape security adjacent index changed obviously. The landscape fragile index of nine cities showed a decreasing trend; however, the landscape security adjacent index has been increasing; (2) from 1990 to 2005, landscape ecology of the cities of Zhuhai and Huizhou maintained a good security situation. However, there was a relatively low value of ecological security in the cities of Dongguan and Foshan. Except for Foshan and Guangzhou, whose landscape ecological security situation were slightly improved, the cities had reduced
Jiahang Yuan
2017-01-01
Full Text Available In consideration of the interaction among attributes and the influence of decision makers’ risk attitude, this paper proposes an intuitionistic trapezoidal fuzzy aggregation operator based on Choquet integral and prospect theory. With respect to a multiattribute group decision-making problem, the prospect value functions of intuitionistic trapezoidal fuzzy numbers are aggregated by the proposed operator; then a grey relation-projection pursuit dynamic cluster method is developed to obtain the ranking of alternatives; the firefly algorithm is used to optimize the objective function of projection for obtaining the best projection direction of grey correlation projection values, and the grey correlation projection values are evaluated, which are applied to classify, rank, and prefer the alternatives. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible.
ESTIMATING PROJECT DEVELOPMENT EFFORT USING CLUSTERED REGRESSION APPROACH
Geeta Nagpal
2013-02-01
Full Text Available Due to the intangible nature of “software”, accurate and reliable software effort estimation is a challenge in the software Industry. It is unlikely to expect very accurate estimates of software development effort because of the inherent uncertainty in software development projects and the complex and dynamic interaction of factors that impact software development. Heterogeneity exists in the software engineering datasets because data is made available from diverse sources. This can be reduced by defining certain relationship between the data values by classifying them into different clusters. This study focuses on how the combination of clustering and regression techniques can reduce the potential problems in effectiveness of predictive efficiency due to heterogeneity of the data. Using a clustered approach creates the subsets of data having a degree of homogeneity that enhances prediction accuracy. It was also observed in this study that ridge regression performs better than other regression techniques used in the analysis.
Pires, Carlos A. L.; Ribeiro, Andreia F. S.
2017-02-01
We develop an expansion of space-distributed time series into statistically independent uncorrelated subspaces (statistical sources) of low-dimension and exhibiting enhanced non-Gaussian probability distributions with geometrically simple chosen shapes (projection pursuit rationale). The method relies upon a generalization of the principal component analysis that is optimal for Gaussian mixed signals and of the independent component analysis (ICA), optimized to split non-Gaussian scalar sources. The proposed method, supported by information theory concepts and methods, is the independent subspace analysis (ISA) that looks for multi-dimensional, intrinsically synergetic subspaces such as dyads (2D) and triads (3D), not separable by ICA. Basically, we optimize rotated variables maximizing certain nonlinear correlations (contrast functions) coming from the non-Gaussianity of the joint distribution. As a by-product, it provides nonlinear variable changes `unfolding' the subspaces into nearly Gaussian scalars of easier post-processing. Moreover, the new variables still work as nonlinear data exploratory indices of the non-Gaussian variability of the analysed climatic and geophysical fields. The method (ISA, followed by nonlinear unfolding) is tested into three datasets. The first one comes from the Lorenz'63 three-dimensional chaotic model, showing a clear separation into a non-Gaussian dyad plus an independent scalar. The second one is a mixture of propagating waves of random correlated phases in which the emergence of triadic wave resonances imprints a statistical signature in terms of a non-Gaussian non-separable triad. Finally the method is applied to the monthly variability of a high-dimensional quasi-geostrophic (QG) atmospheric model, applied to the Northern Hemispheric winter. We find that quite enhanced non-Gaussian dyads of parabolic shape, perform much better than the unrotated variables in which concerns the separation of the four model's centroid regimes
Sparse Regression by Projection and Sparse Discriminant Analysis
Qi, Xin
2015-04-03
© 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.
Projection-type estimation for varying coefficient regression models
Lee, Young K; Park, Byeong U; 10.3150/10-BEJ331
2012-01-01
In this paper we introduce new estimators of the coefficient functions in the varying coefficient regression model. The proposed estimators are obtained by projecting the vector of the full-dimensional kernel-weighted local polynomial estimators of the coefficient functions onto a Hilbert space with a suitable norm. We provide a backfitting algorithm to compute the estimators. We show that the algorithm converges at a geometric rate under weak conditions. We derive the asymptotic distributions of the estimators and show that the estimators have the oracle properties. This is done for the general order of local polynomial fitting and for the estimation of the derivatives of the coefficient functions, as well as the coefficient functions themselves. The estimators turn out to have several theoretical and numerical advantages over the marginal integration estimators studied by Yang, Park, Xue and H\\"{a}rdle [J. Amer. Statist. Assoc. 101 (2006) 1212--1227].
FU QIANG; XIE YONGGANG; WEI ZIMIN
2003-01-01
A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.
Two Projection Pursuit Algorithms for Machine Learning under Non-Stationarity
Blythe, Duncan A J
2011-01-01
This thesis derives, tests and applies two linear projection algorithms for machine learning under non-stationarity. The first finds a direction in a linear space upon which a data set is maximally non-stationary. The second aims to robustify two-way classification against non-stationarity. The algorithm is tested on a key application scenario, namely Brain Computer Interfacing.
Mabb, David; Parekh, Manisha; Dayanita, Dayanita Singh; Audiobombing Crew,
2011-01-01
Nature Morte is pleased to announce „Serial Pursuits,“ a group exhibition in which recent works in various media by David Mabb, Manisha Parekh, Dayanita Singh and Audiobombing Crew will be brought together to present an exploration of art works created as sets or in sequences. The highlight of the opening night will be a performance by Audiobombing Crew. Founded by Markus Zull and Stephan Ebersthäuser in 2003, the sound art collective creates serial sound loops, which are collaged togethe...
Early cost estimating for road construction projects using multiple regression techniques
Ibrahim Mahamid
2011-12-01
Full Text Available The objective of this study is to develop early cost estimating models for road construction projects using multiple regression techniques, based on 131 sets of data collected in the West Bank in Palestine. As the cost estimates are required at early stages of a project, considerations were given to the fact that the input data for the required regression model could be easily extracted from sketches or scope definition of the project. 11 regression models are developed to estimate the total cost of road construction project in US dollar; 5 of them include bid quantities as input variables and 6 include road length and road width. The coefficient of determination r2 for the developed models is ranging from 0.92 to 0.98 which indicate that the predicted values from a forecast models fit with the real-life data. The values of the mean absolute percentage error (MAPE of the developed regression models are ranging from 13% to 31%, the results compare favorably with past researches which have shown that the estimate accuracy in the early stages of a project is between ±25% and ±50%.
Bracegirdle, Thomas J. [British Antarctic Survey, Cambridge (United Kingdom); Stephenson, David B. [University of Exeter, Mathematics Research Institute, Exeter (United Kingdom); NCAS-Climate, Reading (United Kingdom)
2012-12-15
This study presents projections of twenty-first century wintertime surface temperature changes over the high-latitude regions based on the third Coupled Model Inter-comparison Project (CMIP3) multi-model ensemble. The state-dependence of the climate change response on the present day mean state is captured using a simple yet robust ensemble linear regression model. The ensemble regression approach gives different and more precise estimated mean responses compared to the ensemble mean approach. Over the Arctic in January, ensemble regression gives less warming than the ensemble mean along the boundary between sea ice and open ocean (sea ice edge). Most notably, the results show 3 C less warming over the Barents Sea ({proportional_to} 7 C compared to {proportional_to} 10 C). In addition, the ensemble regression method gives projections that are 30 % more precise over the Sea of Okhostk, Bering Sea and Labrador Sea. For the Antarctic in winter (July) the ensemble regression method gives 2 C more warming over the Southern Ocean close to the Greenwich Meridian ({proportional_to} 7 C compared to {proportional_to} 5 C). Projection uncertainty was almost half that of the ensemble mean uncertainty over the Southern Ocean between 30 W to 90 E and 30 % less over the northern Antarctic Peninsula. The ensemble regression model avoids the need for explicit ad hoc weighting of models and exploits the whole ensemble to objectively identify overly influential outlier models. Bootstrap resampling shows that maximum precision over the Southern Ocean can be obtained with ensembles having as few as only six climate models. (orig.)
Zhao, Y.; Su, X. H.; Wang, M. H.; Li, Z. Y.; Li, E. K.; Xu, X.
2017-08-01
Water resources vulnerability control management is essential because it is related to the benign evolution of socio-economic, environmental and water resources system. Research on water resources system vulnerability is helpful to realization of water resources sustainable utilization. In this study, the DPSIR framework of driving forces-pressure–state–impact-response was adopted to construct the evaluation index system of water resources system vulnerability. Then the co-evolutionary genetic algorithm and projection pursuit were used to establish evaluation model of water resources system vulnerability. Tengzhou City in Shandong Province was selected as a study area. The system vulnerability was analyzed in terms of driving forces, pressure, state, impact and response on the basis of the projection value calculated by the model. The results show that the five components all belong to vulnerability Grade II, the vulnerability degree of impact and state were higher than other components due to the fierce imbalance in supply-demand and the unsatisfied condition of water resources utilization. It is indicated that the influence of high speed socio-economic development and the overuse of the pesticides have already disturbed the benign development of water environment to some extents. While the indexes in response represented lower vulnerability degree than the other components. The results of the evaluation model are coincident with the status of water resources system in the study area, which indicates that the model is feasible and effective.
Shin, Yoonseok
2015-01-01
Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.
Yoonseok Shin
2015-01-01
Full Text Available Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.
Bulcock, J. W.; And Others
Multicollinearity refers to the presence of highly intercorrelated independent variables in structural equation models, that is, models estimated by using techniques such as least squares regression and maximum likelihood. There is a problem of multicollinearity in both the natural and social sciences where theory formulation and estimation is in…
Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh
2016-05-01
The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm (Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations
Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh
2017-08-01
The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ( Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations
基于投影寻踪的Web软件复杂性度量%Web software complexity metrics based on projection pursuit
曾一; 胡小威; 李鹃
2012-01-01
传统的软件复杂性度量方法主要是针对C/C++、Ada等语言开发的非Web应用.以面向对象的基于Struts框架的Web软件为研究对象,提出了适合于Web-Struts软件的3个方面的复杂性度量指标,并提出了一种基于带交叉算子人工鱼群和投影寻踪(PP)算法的Web应用软件复杂性度量方法.把Web软件多个复杂性度量指标综合成一维综合投影值,利用样本数据求解最佳投影方向,确定评价等级的综合投影值区间,根据测试样本综合投影值与区间值比较,获得综合评价结果.实例评价结果表明,所提方法具有较强的适用性和应用性.%Web software complexity metrics does play a very important role in the software development. The traditional software complexity metrics method mainly targets on the non-Web applications which use language like C/C + + and Ada. This paper took object-oriented Web software based on Struts framework as research subject and put forward three complexity metrics suitable for the Web-Struts software. Besides, this paper also proposed a method for computing Web software complexity metrics based on Artificial Fish Swarm Algorithm ( AFSA) with cross operator and Projection Pursuit ( PP) algorithm. After integrating multiple complexity metrics into one-dimension comprehensive projection value, the optimized projection direction could be acquired through sample data. Then the comprehensive projection value of evaluation grades could also be determined. According to the comparison between the comprehensive projection values of the testing samples and the interval of level, the comprehensive metrics result could be finally obtained. The example evaluation results prove the feasibility and effectiveness of the proposed method.
A.Muthukumaravel
2011-08-01
Full Text Available This paper presents implementation of locally weighted projection regression (LWPR network method for concurrency control while developing dial of a fork using Autodesk inventor 2008. The LWPR learns the objects and the type of transactions to be done based on which node in the output layer of the network exceeds a threshold value. Learning stops once all the objects are exposed to LWPR. During testing performance, metrics are analyzed. We have attempted to use LWPR for storing lock information when multi users are working on computer Aided Design (CAD. The memory requirements of the proposed method are minimal in processing locks during transaction.
Min Ge
2017-01-01
Full Text Available Clarification of initial water rights is the basis and prerequisite for a water rights trade-off market and also an effective solution to the problem of water scarcity and water conflicts. According to the new requirements for the most stringent water resources management in China, an initial provincial water rights allocation model is proposed. Firstly, based on analysis of multiple principles for initial provincial water rights allocation including total water use, water use efficiency, water quality of water function zones, regional coordination and sharing, an index system of initial provincial water rights allocation is designed. Secondly, according to dynamic projection pursuit technique, an initial provincial water rights allocation model with the total water use control is set up. Moreover, the self-adaptive chaotic optimization algorithm is applied to tackle the model. Finally, a case study of Taihu Basin is adopted. Considering the multiple scenarios of three different water frequencies (50%, 75% and 90% and planning year 2030, the empirical results show Jiangsu Province always obtains the most initial water rights. When the developing situation of provinces are given more consideration, Shanghai should acquire more initial water rights than Zhejiang Province; but when the dynamic increment evolving trend of provinces is taken more into account, Shanghai should obtain less initial water rights than Zhejiang Province. The case about Taihu Lake further verifies the feasibility and effectiveness of the proposed model and provides a multiple-scenarios decision making support for entitling the initial water rights with the most stringent water resources management constrains in Taihu Basin.
基于投影寻踪分析的芯片硬件木马检测%Hardware Trojans detection based on projection pursuit
张鹏; 王新成; 周庆
2013-01-01
提出一种利用芯片旁路泄漏信息的硬件木马无损检测方法，通过基于绝对信息散度指标的投影寻踪技术，将芯片运行过程中产生的高维旁路信号投影变换到低维子空间，在信息损失尽量小的前提下发现原始数据中的分布特征，从而实现芯片旁路信号特征提取与识别。针对示例性高级加密标准(AES-128)木马电路的检测实验表明，该技术可以有效分辨基准芯片与硬件木马测试芯片之间的旁路信号特征差异，实现硬件木马检测。%A novel hardware Trojans detection technique using the side channel signals of chips was proposed. Based on the projection pursuit with absolute information divergence index, this technique could find out the data structure enables reflect high dimension special rules without obvious information loss, so as to attain the goal of feature abstraction and identification on side channel signals of IC chips. The detection experiment against an exemplary AES-128 hardware Trojan circuit showed that the technique could distinguish the difference of side channel signal’s feature between the ge-nuine chip and tested chip, and consequently could detect the existence of the hardware Trojan.
Magura, Stephen; Cleland, Charles M.; Tonigan, J. Scott
2013-01-01
Objective: The objective of the study is to determine whether Alcoholics Anonymous (AA) participation leads to reduced drinking and problems related to drinking within Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity), an existing national alcoholism treatment data set. Method: The method used is structural equation modeling of panel data with cross-lagged partial regression coefficients. The main advantage of this technique for the analysis of AA outcomes is that potential reciprocal causation between AA participation and drinking behavior can be explicitly modeled through the specification of finite causal lags. Results: For the outpatient subsample (n = 952), the results strongly support the hypothesis that AA attendance leads to increases in alcohol abstinence and reduces drinking/problems, whereas a causal effect in the reverse direction is unsupported. For the aftercare subsample (n = 774), the results are not as clear but also suggest that AA attendance leads to better outcomes. Conclusions: Although randomized controlled trials are the surest means of establishing causal relations between interventions and outcomes, such trials are rare in AA research for practical reasons. The current study successfully exploited the multiple data waves in Project MATCH to examine evidence of causality between AA participation and drinking outcomes. The study obtained unique statistical results supporting the effectiveness of AA primarily in the context of primary outpatient treatment for alcoholism. PMID:23490566
基于混合蛙跳投影寻踪模型的水利水电规划方案优选%Hydropower Planning Scheme preferred Based on Projection Pursuit Model SFLA
张博; 许娇娇
2015-01-01
介绍了投影寻踪方法的基本原理, 并引入混合蛙跳算法求解投影寻踪模型中最佳投影方向优化问题,建立基于混合蛙跳算法的投影寻踪模型, 并将其应用于水利水电规划方案优选问题, 结果表明该方法不仅避免了常规方法主观赋权的任意性, 而且计算简单、 使用范围广, 具有良好的有效性与适用性.%The concept and postulate of the Projection Pursuit was introduced ,and Shuffled Frog Leaping Al-gorithm was introduced to solve the optimal projection direction optimization problem ,then Projection Pursuit model based on SFLA was established and applied for hydropower planning scheme optimization problems ,the evaluation results indicated that this method not only avoids arbitrariness of empowerment in traditional method,but also has a simple calculation and wide range ,as well as good validity and applicability.
2009-12-18
analysis of the equilibria based on linearization of the shape dynamics. In [10], the authors extend their analysis to incorporate feedback control...differentiable curves in R2, deriving our dynamics from the natural Frenet frame equations (see, e.g., [5] for details). (A three- dimensional analysis of...cyclic pursuit formulated in terms of the natural Frenet frame equations is a topic of ongoing work.) As is depicted in figure 1, we let ri denote the
David P. Schmitt et al.
2017-05-01
Full Text Available Previous studies have documented links between sub-clinical narcissism and the active pursuit of short-term mating strategies (e.g., unrestricted sociosexuality, marital infidelity, mate poaching. Nearly all of these investigations have relied solely on samples from Western cultures. In the current study, responses from a cross-cultural survey of 30,470 people across 53 nations spanning 11 world regions (North America, Central/South America, Northern Europe, Western Europe, Eastern Europe, Southern Europe, Middle East, Africa, Oceania, Southeast Asia, and East Asia were used to evaluate whether narcissism (as measured by the Narcissistic Personality Inventory; NPI was universally associated with short-term mating. Results revealed narcissism scores (including two broad factors and seven traditional facets as measured by the NPI were functionally equivalent across cultures, reliably associating with key sexual outcomes (e.g., more active pursuit of short-term mating, intimate partner violence, and sexual aggression and sex-related personality traits (e.g., higher extraversion and openness to experience. Whereas some features of personality (e.g., subjective well-being were universally associated with socially adaptive facets of Narcissism (e.g., self-sufficiency, most indicators of short-term mating (e.g., unrestricted sociosexuality and marital infidelity were universally associated with the socially maladaptive facets of narcissism (e.g., exploitativeness. Discussion addresses limitations of these cross-culturally universal findings and presents suggestions for future research into revealing the precise psychological features of narcissism that facilitate the strategic pursuit of short-term mating.
Yoonseok Shin
2015-01-01
Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stag...
田铮; 文奇; 金子
2001-01-01
The convergence property of the projection pursuit learning network (PPLN) that is used to approximate to non-linear autoregrcssion is studied in this paper. The authros prove that PPLN can approximate to non-linear autoregression at any given precision in Lk space, where k is integer. The learning strategy and calculative procedures of PPLN's, which are used to establishthe models of non-linear time series {Xt } and forecast the subsequent behavior of {Xt}, are also presented. Using PPLN, the Wolfer sunspont number(1749-1894), Canada lvnx data(1821-1924) and Xi'an data(0-360) are fitted. Furthermore, the predictors for the above three kinds of data are also pre sented, respectively. Finally, we compare the performance the projection pursuit learning network not only with that of backpropagation learning (BPLN) but also with that of the threshold model. It is shown that the projection pursuit learning networks perform well and compare favorably to BPLN and the threshold model.%本文研究非线性自回归模型投影寻踪学习网络逼近的收敛性，证明了在Lk(k为正整数)空间上，投影寻踪学习网络可以以任意精度逼近非线性自回归模型，给出基于投影寻踪学习网络的非线性时间序列模型建模和预报的计算方法和应用实例，对太阳黑子数据、山猫数据及西安数据进行了拟合和预报，将其结果与改进的BP网和门限自回归模型相应的结果进行比较，结果表明基于投影寻踪学习网络的非线性时间序列的建模和预报方法是一类行之有效的方法。
袁尧; 刘超
2013-01-01
针对泵站优化运行计算时最优解评价指标单一的问题,建立了包含机组开停机约束的泵站优化运行数学模型和运行方案选优的投影寻踪决策模型.提出了求解泵站多机组优化运行模型的蚁群算法,并通过分析模型的特性改进了算法中启发式信息和信息素更新方式.对江都四站多机组日优化运行计算的结果显示,变量同等离散的情况下,利用蚁群算法优化的结果比用动态规划逐次逼近法优化的结果节省了2.8％的电费,前者相比设计工况运行时节省了29.2％的电费,且蚁群算法优化结果对应的运行方案中叶片调节次数少,机组运行时间短；方案选优时投影寻踪决策模型能够兼顾多个评价指标的优选,得到的运行方案不仅运行成本低,且更合理,更贴切于日常运行,可见改进后的蚁群算法结合投影寻踪决策模型在泵站优化运行及相近的领域有较大的实用价值.%Usually the evaluation index of optimal pump operation solution is single. An optimal pump operation model which contained the constraint of start-stop pump unit was developed, and projection pursuit evaluation method for scheme optimization was proposed. The ant colony optimization algorithm was used to calculate the model. The heuristic information and the pheromone trail update method were improved by analyzing characters of the model for better performances. A calculation example for the No. 4 Jiangdu pumping station was conducted. The results from ant colony optimization algorithm showed that 29. 2% of energy fee could be saved under the designed operation condition, which was compared with the result from dynamic programming with successive approximation algorithm under the same discrete condition, and was better with 2. 8% of the result from dynamic programming. The results from ant colony optimization algorithm had less times of the blade adjusting, and shorter operating time of the pumps
Generalized Orthogonal Matching Pursuit
Wang, Jian; Shim, Byonghyo
2011-01-01
As a greedy algorithm to recover sparse signals from compressed measurements, the orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we introduce an extension of the orthogonal matching pursuit (gOMP) for pursuing efficiency in reconstructing sparse signals. Our approach, henceforth referred to as generalized OMP (gOMP), is literally a generalization of the OMP in the sense that multiple indices are identified per iteration. Owing to the selection of multiple "correct" indices, the gOMP algorithm is finished with much smaller number of iterations compared to the OMP. We show that the gOMP can perfectly reconstruct any $K$-sparse signals ($K > 1$), provided that the sensing matrix satisfies the RIP with $\\delta_{NK} < \\frac{\\sqrt{N}}{\\sqrt{K} + 2 \\sqrt{N}}$. We also demonstrate by empirical simulations that the gOMP has excellent recovery performance comparable to $\\ell_1$-minimization technique with fast processing speed and competitive computational com...
张目; 周宗放
2011-01-01
提出一种基于投影寻踪和最优分割的企业信用评级模型.该模型运用投影寻踪对样本企业进行信用综合评分,将信用综合得分由大到小排序,生成有序样品序列；利用最优分割法对有序样品进行聚类,得出明确的聚类结果；将最优分割点对应的信用综合得分作为划分信用等级的阈值,从而实现对样本企业的信用评级.应用实例证明了该模型的可行性和有效性.%A new credit rating model for enterprises based on projection pursuit and optimal partition is presented in this paper. Using projection pursuit, the comprehensive credit score of each sample is obtained. After sorting the comprehensive credit score descending, the ordered sample series is generated. A clustering analysis of the ordered samples is carried out with the optimal partition method, so the clustering results are obtained definitely. And then, each optimal partition point is regarded as the threshold to divide the credit grades. Finally, the credit ratin'g for enterprises is achieved. Through a specific example, it is proved that the model proposed by this paper is feasible and effective.
楼文高; 楼际通; 宋雷娟; 王浪庆
2015-01-01
从上海市某区386家中小企业申报的15项税收指标数据中筛选出对判定企业纳税情况具有重要影响的10个评价指标，并将全部386个样本分成性质相似的建模样本和测试样本（其中测试样本个数占45％），建立了基于投影寻踪分类（PPC）技术的税务稽查评价模型。与多元线性回归（MLR）、判别分析（MDA）、Logistic 和支持向量机（SVM）模型相比，PPC 模型的识别错误率最低，建模样本和测试样本的平均分类错误率低于6％，改进型 PPC 模型包含的评价指标少，两类错误率很接近，非常适用于实际企业的税务稽查评估研究和实践。对339家待判断企业纳税情况的判定结果研究表明，建立的改进型 PPC 模型具有很好的泛化能力和鲁棒性。%Based on the 15 variables’(indexes’)tax-reporting data of 386 wooden-furniture manufacturing small-and medium-sized enterprises (WFMSMEs)located in some districts of Shanghai city,the ten variables mainly influencing the tax-checking situation (tax evasion or compliance)of the 386 WFMSMEs were obtained by applying sensitivity analysis method (SAM)for selecting input variables.The modelling set data and testing set data (about taking up 45%)with similar character-istics-similar mean values and variance-were divided using self-organizing map (SOM)approach.The practical,feasible and effective projection pursuit clustering (PPC)model for tax-checking assessment was thus established.Compared with the mult-ivariate linear regression (MLR),the multivariate discriminant analysis (MDA),Logistic and the support vector machine (SVM),the established PPC model possesses the most accurate and the lowest classification-error percentage (CEP)of the models.The mean CEP of modelling set data and the testing set data is lower than 6%.The improved PPC model including fe-wer variables is thus suitable to tax-checking assessment and research.The tax-checking situation of
董丽丽; 于苗; 徐淑琴
2015-01-01
针对粒子群算法局部搜索能力较弱和存在早熟收敛的问题，为了有效地控制粒子群算法的全局搜索和局部搜索，提出了将线性递减权重引入到粒子群优化算法中。该算法是从随机解出发，通过追随当前搜索到的最优值来寻找全局最优解，增加了粒子群算法的局部搜索能力。将其算法优化投影寻踪模型，以此构建了线性递减权重粒子群优化投影寻踪模型，将该模型应用到土坝护坡模式优化评价中，选取9个指标作为评判因子，提出适合该地区的土坝护坡优化模式。结果表明：线性递减权重粒子群优化投影寻踪模型可以有效地找到最佳投影方向，计算投影值，根据投影指标值的大小可对方案进行优选。利用该模型对土坝护坡模式进行综合评价是切实可行的。该算法以其实现容易、精度高、收敛快等优点，并且在解决实际问题中展示的优越性，在工程优化领域具有广泛的应用前景。%To overcome the lower local search ability and the problem of premature convergence in par-ticle swarm optimization,and efficiently control the global and local search of particle swarm optimiza-tion,particle swarm optimization with linearly decreasing weight was proposed.It started from random solutions,which followed the current search for the optimal value to find the global optimum,increa-sing the local search ability of the algorithm.By optimizing the algorithm with the projection pursuit model,particle swarm with linearly decreasing weight optimized projection pursuit model was estab-lished.The model was applied to optimize evaluation of dam slope protection,and 9 indicators were reselected as evaluation factors;as a result,an area-suitable optimization model of dam slope protection was proposed.The results show that using particle swarm with linearly decreasing weight optimized pro-jection pursuit model can effectively find out the best
The effects of smooth pursuit adaptation on the gain of visuomotor transmission in monkeys
Seiji eOno
2013-12-01
Full Text Available Smooth pursuit eye movements are supported by visual-motor systems, where visual motion information is transformed into eye movement commands. Adaptation of the visuomotor systems for smooth pursuit is an important factor to maintain pursuit accuracy and high acuity vision. Short-term adaptation of initial pursuit gain can be produced experimentally using by repeated trials of a step-ramp tracking with two different velocities (double-step paradigm that step-up (10–30 °/s or step-down (20–5 °/s. It is also known that visuomotor gain during smooth pursuit is regulated by a dynamic gain control mechanism by showing that eye velocity evoked by a target perturbation during pursuit increases bidirectionally when ongoing pursuit velocity is higher. However, it remains uncertain how smooth pursuit adaptation alters the gain of visuomotor transmission. Therefore, a single cycle of sinusoidal motion (2.5 Hz, ± 10 °/s was introduced during step-ramp tracking pre- and post-adaptation to determine whether smooth pursuit adaptation affects the perturbation response. The results showed that pursuit adaptation had a significant effect on the perturbation response that was specific to the adapted direction. These results indicate that there might be different visuomotor mechanisms between adaptation and dynamic gain control. Furthermore, smooth pursuit adaptation altered not only the gain of the perturbation response, but also the gain slope (regression curve at different target velocities (5, 10 and 15 °/s. Therefore, pursuit adaptation could affect the dynamic regulation of the visuomotor gain at different pursuit velocities.
The projection of world geothermal energy consumption from time series and regression model
Simanullang, Elwin Y.; Supriatna, Agus; Supriatna, Asep K.
2015-12-01
World population growth has many impacts on human live activities and other related aspects. One among the aspects is the increase of the use of energy to support human daily activities, covering industrial aspect, transportation, domestic activities, etc. It is plausible that the higher the population size in a country the higher the needs for energy to support all aspects of human activities in the country. Considering the depletion of petroleum and other fossil-based energy, recently there is a tendency to use geothermal as other source of energy. In this paper we will discuss the prediction of the world consumption of geothermal energy by two different methods, i.e. via the time series of the geothermal usage and via the time series of the geothermal usage combined with the prediction of the world total population. For the first case, we use the simple exponential smoothing method while for the second case we use the simple regression method. The result shows that taking into account the prediction of the world population size giving a better prediction to forecast a short term of the geothermal energy consumption.
Wu, W.; Chen, G. Y.; Kang, R.; Xia, J. C.; Huang, Y. P.; Chen, K. J.
2017-07-01
During slaughtering and further processing, chicken carcasses are inevitably contaminated by microbial pathogen contaminants. Due to food safety concerns, many countries implement a zero-tolerance policy that forbids the placement of visibly contaminated carcasses in ice-water chiller tanks during processing. Manual detection of contaminants is labor consuming and imprecise. Here, a successive projections algorithm (SPA)-multivariable linear regression (MLR) classifier based on an optimal performance threshold was developed for automatic detection of contaminants on chicken carcasses. Hyperspectral images were obtained using a hyperspectral imaging system. A regression model of the classifier was established by MLR based on twelve characteristic wavelengths (505, 537, 561, 562, 564, 575, 604, 627, 656, 665, 670, and 689 nm) selected by SPA , and the optimal threshold T = 1 was obtained from the receiver operating characteristic (ROC) analysis. The SPA-MLR classifier provided the best detection results when compared with the SPA-partial least squares (PLS) regression classifier and the SPA-least squares supported vector machine (LS-SVM) classifier. The true positive rate (TPR) of 100% and the false positive rate (FPR) of 0.392% indicate that the SPA-MLR classifier can utilize spatial and spectral information to effectively detect contaminants on chicken carcasses.
Stable Principal Component Pursuit
Zhou, Zihan; Wright, John; Candes, Emmanuel; Ma, Yi
2010-01-01
In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a high-dimensional data matrix despite both small entry-wise noise and gross sparse errors. Recently, it has been shown that a convex program, named Principal Component Pursuit (PCP), can recover the low-rank matrix when the data matrix is corrupted by gross sparse errors. We further prove that the solution to a related convex program (a relaxed PCP) gives an estimate of the low-rank matrix that is simultaneously stable to small entrywise noise and robust to gross sparse errors. More precisely, our result shows that the proposed convex program recovers the low-rank matrix even though a positive fraction of its entries are arbitrarily corrupted, with an error bound proportional to the noise level. We present simulation results to support our result and demonstrate that the new convex program accurately recovers the principal components (the low-rank matrix) under quite broad conditions. To our knowledge, this is...
任永泰; 李丽
2011-01-01
利用基于极大熵准则赋权和基于实数加速遗传算法的投影寻踪方法相结合的组合附权法确定了各预警指标的权重；采用层次分析法计算水资源可持续利用复合系统中各子系统所占权重；利用综合评价模型计算出哈尔滨市水资源可持续发展指数；最终得到哈尔滨市水资源可持续利用预警结果.%The weights of each warning index are determined by combination enables law which is based on the maximum entropy criterion empowerment and projection pursuit method of real accelerating genetic algorithm; Using analytic hierarchy process to calculate the weights of each subsystem in composite system of water resources sustainable utilization; Sustainable development index of Harbin water resources is calculated by using comprehensive evaluation model; Warning results of Harbin water resources sustainable utilization are got eventually.
侯秀玲; 周益民; 周密; 王绍俊
2012-01-01
[Objective] The purpose of this project was to provide a scientific basis for preventing and controlling pollution by choosing different methods basing on particle swarm algorithm projection pursuit model analysis of farmland soil pollution. [Method] The sewage irrigation area from Shihezi city was chosen as the research object, surface soil was collected and various elements analysis was conducted. Through a number of indicators of soil contamination as projection parameters, the projection direction was determined. The projection index reflected the characteristics of pollutants in the soil of sewage irrigation areas. The method can avoid the artificial disturbance and acquire preferable effect. [Result] The results showed that soil pollution was mainly from nickel and chromium, and showed a tendency of soil sampling points reduction and soil environmental comprehensive quality deterioration. [ Conclusion ] This study determined the prevention and control of soil pollution in Shihezi River.%[目的]利用基于粒子群算法的投影寻踪模型分析农田土壤污染问题,为农田土壤污染选用不同的污染防治方法提供科学依据.[方法]以石河子总场城市污水灌溉区为研究对象,采集表层土壤样品,对多种元素进行分析.以多个土壤污染指标作为投影参数来寻求其投影方向,由投影指标函效来反映污灌区土壤污染物特征,避免人为赋予权重的干扰.[结果]土壤污染以镍和铬为主要污染因子,并呈现随土壤环境质量综合状况的变差,土壤采样点数减少的规律.[结论]石河子总场对土壤污染影响最大的是污染物是镍和铬,对土壤的污染顺序为:Ni ＞Cd ＞Zn＞ Cu ＞V＞ As＞ Pb＞ Mn＞F＞Se＞Hg ＞Cr.确定了石河子总场农田土壤污染防治方向和方法.
Stevens, Jon Scott; Gleitman, Lila R; Trueswell, John C; Yang, Charles
2017-04-01
We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed Pursuit, uses an associative learning mechanism to estimate word-referent probability but pursues and tests the best referent-meaning at any given time. Pursuit is found to perform as well as global models under many conditions extracted from naturalistic corpora of parent-child interactions, even though the model maintains far less information than global models. Moreover, Pursuit is found to best capture human experimental findings from several relevant cross-situational word-learning experiments, including those of Yu and Smith (), the paradigm example of a finding believed to support fully global cross-situational models. Implications and limitations of these results are discussed, most notably that the model characterizes only the earliest stages of word learning, when reliance on the co-occurring referent world is at its greatest. Copyright © 2016 Cognitive Science Society, Inc.
曹永强; 马静; 李香云; 柯丽娜; 伊吉美
2011-01-01
Drought can directly affect agricultural output and food shortages. Its continuous accumulation can result in significant land degradation, water resources depletion, and environmental damage, which can restrict the sustainable development of agriculture. The status of agricultural production is prominent in Dalian. It often suffers from drought disaster, which has restrained agricultural development in recent years. Unraveling characteristics of agricultural drought of Dalian is therefore critical. The authors synthetically considered mechanisms of various interactions of agricultural drought, introduced reduced-order thoughts of projection, and built an agricultural drought model by the Projection Pursuit Technique to evaluate agricultural drought vulnerability of Dalian. A vulnerability evaluation index system was built, including population density, agricultural output value proportion, wet area proportion, precipitation, sowing area ratio, the agricultural population proportion, food production per capita, irrigation index, net income of farmer average per capita, and agricultural fertilizer quantity per unit area. We then selected the best projection direction, took characteristic quantities of direction as the mete yard, and evaluated the agricultural drought vulnerability of seven agricultural areas in Dalian based on the panel dataset during the period 2000-2007. Characteristics of variations in spatial-temporal differences of vulnerability assessment were comprehensively analyzed. Then, the zonal map of agricultural drought vulnerability of the study area was drawn. The following conclusions were drawn. The average values of agricultural drought vulnerability assessment in descending order are Zhnanghe City, Pulandian City, Wafangdian City, Jinzhou District, Lvshunkou District, Changhai County and Ganjingzi District. The agricultural drought vulnerability of the north is higher than the south and central Dalian. Results show that the Projection Pursuit
EMDR effects on pursuit eye movements.
Kapoula, Zoi; Yang, Qing; Bonnet, Audrey; Bourtoire, Pauline; Sandretto, Jean
2010-05-21
This study aimed to objectivize the quality of smooth pursuit eye movements in a standard laboratory task before and after an Eye Movement Desensitization and Reprocessing (EMDR) session run on seven healthy volunteers. EMDR was applied on autobiographic worries causing moderate distress. The EMDR session was complete in 5 out of the 7 cases; distress measured by SUDS (Subjective Units of Discomfort Scale) decreased to a near zero value. Smooth pursuit eye movements were recorded by an Eyelink II video system before and after EMDR. For the five complete sessions, pursuit eye movement improved after their EMDR session. Notably, the number of saccade intrusions-catch-up saccades (CUS)-decreased and, reciprocally, there was an increase in the smooth components of the pursuit. Such an increase in the smoothness of the pursuit presumably reflects an improvement in the use of visual attention needed to follow the target accurately. Perhaps EMDR reduces distress thereby activating a cholinergic effect known to improve ocular pursuit.
Highly Scalable Matching Pursuit Signal Decomposition Algorithm
National Aeronautics and Space Administration — In this research, we propose a variant of the classical Matching Pursuit Decomposition (MPD) algorithm with significantly improved scalability and computational...
Pursuit-evasion differential games
Yavin, Y
1987-01-01
Twenty papers are devoted to the treatment of a wide spectrum of problems in the theory and applications of dynamic games with the emphasis on pursuit-evasion differential games. The problem of capturability is thoroughly investigated, also the problem of noise-corrupted (state) measurements. Attention is given to aerial combat problems and their attendant modelling issues, such as variable speed of the combatants, the three-dimensionality of physical space, and the combat problem, i.e. problems related to 'role determination'.
Dynamics of aerial target pursuit
Pal, S.
2015-12-01
During pursuit and predation, aerial species engage in multitasking behavior that involve simultaneous target detection, tracking, decision-making, approach and capture. The mobility of the pursuer and the target in a three dimensional environment during predation makes the capture task highly complex. Many researchers have studied and analyzed prey capture dynamics in different aerial species such as insects and bats. This article focuses on reviewing the capture strategies adopted by these species while relying on different sensory variables (vision and acoustics) for navigation. In conclusion, the neural basis of these capture strategies and some applications of these strategies in bio-inspired navigation and control of engineered systems are discussed.
Orthogonal Matching Pursuit with Replacement
Jain, Prateek; Dhillon, Inderjit S
2011-01-01
In this paper, we consider the problem of compressed sensing where the goal is to recover almost all the sparse vectors using a small number of fixed linear measurements. For this problem, we propose a novel partial hard-thresholding operator that leads to a general family of iterative algorithms. While one extreme of the family yields well known hard thresholding algorithms like ITI (Iterative Thresholding with Inversion) and HTP (Hard Thresholding Pursuit), the other end of the spectrum leads to a novel algorithm that we call Orthogonal Matching Pursuit with Replacement (OMPR). OMPR, like the classic greedy algorithm OMP, adds exactly one coordinate to the support at each iteration, based on the correlation with the current residual. However, unlike OMP, OMPR also removes one coordinate from the support. This simple change allows us to prove that OMPR has the best known guarantees for sparse recovery in terms of the Restricted Isometry Property (a condition on the measurement matrix). In contrast, OMP is kn...
Multivariate Adaptive Regression Splines (Preprint)
1990-08-01
characteristics of olive oils as a function of production year by multivariate methods. La Revista Italiana delle Sostanze Grasse, 60, Oct. . Friedman, J...Projection pursuit 76, 817-823. Friedman, J. H. and Wright, M. J. (1981). A nested partitioni: integration. ACM Trans. Math. Software, March. simonious...data. Proc. 1964 ACM Nat. Conf., 517-524. Shumaker, L. L. (1976). Fitting surfaces to scattered data. In Approximation Theory III, G. G. Lorentz, C
崔东文; 梁廷报
2016-01-01
提出湖泊健康评价指标体系和分级标准，构建基于投影寻踪( PP)模型的湖泊健康评价模型，以云南省抚仙湖和星云湖健康评价为例进行实例研究。首先，利用层次分析法( AHP)从水文完整性、物理结构完整性、化学完整性、生物完整性和服务功能完整性5个方面遴选出12个指标，构建3个层次的湖泊健康评价指标体系和5个等级的分级标准；其次，针对PP模型在实际应用中最佳投影方向难以确定以及基本蝙蝠算法( BA)存在早熟收敛等不足，提出一种基于Lévy飞行策略改进的蝙蝠算法( LBA)，通过10个复杂测试函数对该算法进行仿真验证，并与基本BA和粒子群优化( PSO)算法进行对比。最后，利用LBA算法搜寻PP模型最佳投影方向，提出LBA-PP湖泊健康评价模型，并对实例进行评价分析。结果表明：①LBA算法具有较好的收敛精度和全局寻优能力，将LBA算法用于PP模型最佳投影方向的选取，可有效提高PP模型评价精度；②LBA-PP模型对抚仙湖2011—2012年3次调查的评价结果均为“健康”，对星云湖2012年2次调查的评价结果均为“亚健康”。%Taking Fuxian Lake and Xingyun Lake in Yunnan Province health evaluation as an example case, Lake Health Evaluation In-dex System and grading standards is put forward, and lake health evaluation model is built on the basis of projection pursuit ( PP) . First of all, using the analytic hierarchy process ( AHP) to select 12 indexes from 5 aspects of hydrological integrity, physical structure, chemical integrity integrity, integrity and service function of biological integrity, grading standard construction of Lake health evaluation index system of 3 level and 5 level; secondly, according to the optimal projection direction the PP model in the practical application is difficult to determine the basic algorithm and bats ( BA) such as premature convergence and other problems
Hao, Lingxin
2007-01-01
Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao
The pursuit of perfect packing
Weaire, Denis
2000-01-01
In 1998 Thomas Hales dramatically announced the solution of a problem that has long teased eminent mathematicians: what is the densest possible arrangement of identical spheres? The Pursuit of Perfect Packing recounts the story of this problem and many others that have to do with packing things together. The examples are taken from mathematics, physics, biology, and engineering, including the arrangement of soap bubbles in foam, atoms in a crystal, the architecture of the bee''s honeycomb, and the structure of the Giant''s Causeway. Using an informal style and with key references, the book also includes brief accounts of the lives of many of the scientists who devoted themselves to problems of packing over many centuries, together with wry comments on their efforts. It is an entertaining introduction to the field for both specialists and the more general public.
Robust PCA via Outlier Pursuit
Xu, Huan; Sanghavi, Sujay
2010-01-01
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it is nevertheless plagued by a well-known, well-documented sensitivity to outliers. Recent work has considered the setting where each point has a few arbitrarily corrupted components. Yet, in applications of SVD or PCA such as robust collaborative filtering or bioinformatics, malicious agents, defective genes, or simply corrupted or contaminated experiments may effectively yield entire points that are completely corrupted. We present an efficient convex optimization-based algorithm we call Outlier Pursuit, that under some mild assumptions on the uncorrupted points (satisfied, e.g., by the standard generative assumption in PCA problems) recovers the exact optimal low-dimensional subspace, and identifies the corrupted points. Such identification of corrupted points that do not conform to the low-dimensional approximation, is of paramount ...
The pursuit of perfect packing
Weaire, Denis
2008-01-01
Coauthored by one of the creators of the most efficient space packing solution, the Weaire-Phelan structure, The Pursuit of Perfect Packing, Second Edition explores a problem of importance in physics, mathematics, chemistry, biology, and engineering: the packing of structures. Maintaining its mathematical core, this edition continues and revises some of the stories from its predecessor while adding several new examples and applications. The book focuses on both scientific and everyday problems ranging from atoms to honeycombs. It describes packing models, such as the Kepler conjecture, Voronoï decomposition, and Delaunay decomposition, as well as actual structure models, such as the Kelvin cell and the Weaire-Phelan structure. The authors discuss numerous historical aspects and provide biographical details on influential contributors to the field, including emails from Thomas Hales and Ken Brakke. With examples from physics, crystallography, engineering, and biology, this accessible and whimsical bo...
金菊良; 魏一鸣; 付强; 丁晶
2002-01-01
为预测海洋冰情时序这类非线性动力系统,提出了投影寻踪门限自回归(PPTAR)模型.用自相关分析技术确定预测因子,构造了新的投影指标函数,用门限回归(TR)模型描述投影值与预测对象间的非线性关系,并用实码加速遗传算法优化投影指标函数和TR模型参数.实例的计算结果表明,用PPTAR模型预测海洋冰情时序是可行和有效的.PPTAR模型简便、适用性强,克服了目前投影寻踪方法计算量大、编程实现困难的缺点,有助于投影寻踪方法的推广应用,为解决非线性时序复杂预测问题提供了新的途径.
毛鸿才; 杨力行; 姚源松; 陈全家
2001-01-01
用投影寻踪回归技术,对棉花高产栽培二次通用旋转试验的二次项回归系数bjj＞0的"无效"试验数据进行建模和仿真研究,寻找出内在的客观规律,使"无效"试验数据变成了有用的数据.
Pursuit on an Organized Crime Network
Marshak, Charles Z; Bertozzi, Andrea L; D'Orsogña, Maria R
2015-01-01
We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical sim...
Peacock, Thomas
2014-11-01
Orders of magnitude larger than surface waves, and so powerful that their generation impacts the lunar orbit, internal waves, propagating disturbances of a density-stratified fluid, are ubiquitous throughout the ocean and atmosphere. Following the discovery of the phenomenon of ``dead water'' by early Arctic explorers and the classic laboratory visualizations of the curious St. Andrew's Cross internal wave pattern, there has been a resurgence of interest in internal waves, inspired by their pivotal roles in local environmental and global climate processes, and their profound impact on ocean and aerospace engineering. We detail our widespread pursuit of internal waves through theoretical modeling, laboratory experiments and field studies, from the Pacific Ocean one thousand miles north and south of Hawaii, to the South China Sea, and on to the Arctic Ocean. We also describe our recent expedition to surf the most striking internal wave phenomenon of them all: the Morning Glory cloud in remote Northwest Australia. This work was supported by the National Science Foundation through a CAREER Grant OCE-064559 and through Grants OCE-1129757 and OCE-1357434, and by the Office of Naval Research through Grants N00014-09-1-0282, N00014-08-1-0390 and N00014-05-1-0575.
Doing smooth pursuit paradigms in Windows 7
Wilms, Inge Linda
Smooth pursuit eye movements are interesting to study as they reflect the subject’s ability to predict movement of external targets, keep focus and move the eyes appropriately. The process of smooth pursuit requires collaboration between several systems in the brain and the resulting action may p...... in Windows 7 with live capturing of eye movements using a Tobii TX300 eye tracker. In particular, the poster describes the challenges and limitations created by the hardware and the software...
EMDR Effects on Pursuit Eye Movements
Zoi Kapoula; Qing Yang; Audrey Bonnet; Pauline Bourtoire; Jean Sandretto
2010-01-01
This study aimed to objectivize the quality of smooth pursuit eye movements in a standard laboratory task before and after an Eye Movement Desensitization and Reprocessing (EMDR) session run on seven healthy volunteers. EMDR was applied on autobiographic worries causing moderate distress. The EMDR session was complete in 5 out of the 7 cases; distress measured by SUDS (Subjective Units of Discomfort Scale) decreased to a near zero value. Smooth pursuit eye movements were recorded by an Eyelin...
Goal Pursuit in Youth with Chronic Pain
Fisher, Emma; Palermo, Tonya M.
2016-01-01
Children and adolescents frequently experience chronic pain that can disrupt their usual activities and lead to poor physical and emotional functioning. The fear avoidance model of pain with an emphasis on the maladaptive behaviors that lead to activity avoidance has guided research and clinical practice. However, this model does not take into consideration variability in responses to pain, in particular the active pursuit of goals despite pain. This review aims to introduce a novel conceptualization of children’s activity engagement versus avoidance using the framework of goal pursuit. We propose a new model of Goal Pursuit in Pediatric Chronic Pain, which proposes that the child’s experience of pain is modified by child factors (e.g., goal salience, motivation/energy, pain-related anxiety/fear, and self-efficacy) and parent factors (e.g., parent expectations for pain, protectiveness behaviors, and parent anxiety), which lead to specific goal pursuit behaviors. Goal pursuit is framed as engagement or avoidance of valued goals when in pain. Next, we recommend that research in youth with chronic pain should be reframed to account for the pursuit of valued goals within the context of pain and suggest directions for future research. PMID:27879686
Goal Pursuit in Youth with Chronic Pain
Emma Fisher
2016-11-01
Full Text Available Children and adolescents frequently experience chronic pain that can disrupt their usual activities and lead to poor physical and emotional functioning. The fear avoidance model of pain with an emphasis on the maladaptive behaviors that lead to activity avoidance has guided research and clinical practice. However, this model does not take into consideration variability in responses to pain, in particular the active pursuit of goals despite pain. This review aims to introduce a novel conceptualization of children’s activity engagement versus avoidance using the framework of goal pursuit. We propose a new model of Goal Pursuit in Pediatric Chronic Pain, which proposes that the child’s experience of pain is modified by child factors (e.g., goal salience, motivation/energy, pain-related anxiety/fear, and self-efficacy and parent factors (e.g., parent expectations for pain, protectiveness behaviors, and parent anxiety, which lead to specific goal pursuit behaviors. Goal pursuit is framed as engagement or avoidance of valued goals when in pain. Next, we recommend that research in youth with chronic pain should be reframed to account for the pursuit of valued goals within the context of pain and suggest directions for future research.
Goal Pursuit in Youth with Chronic Pain.
Fisher, Emma; Palermo, Tonya M
2016-11-22
Children and adolescents frequently experience chronic pain that can disrupt their usual activities and lead to poor physical and emotional functioning. The fear avoidance model of pain with an emphasis on the maladaptive behaviors that lead to activity avoidance has guided research and clinical practice. However, this model does not take into consideration variability in responses to pain, in particular the active pursuit of goals despite pain. This review aims to introduce a novel conceptualization of children's activity engagement versus avoidance using the framework of goal pursuit. We propose a new model of Goal Pursuit in Pediatric Chronic Pain, which proposes that the child's experience of pain is modified by child factors (e.g., goal salience, motivation/energy, pain-related anxiety/fear, and self-efficacy) and parent factors (e.g., parent expectations for pain, protectiveness behaviors, and parent anxiety), which lead to specific goal pursuit behaviors. Goal pursuit is framed as engagement or avoidance of valued goals when in pain. Next, we recommend that research in youth with chronic pain should be reframed to account for the pursuit of valued goals within the context of pain and suggest directions for future research.
EMDR effects on pursuit eye movements.
Zoi Kapoula
Full Text Available This study aimed to objectivize the quality of smooth pursuit eye movements in a standard laboratory task before and after an Eye Movement Desensitization and Reprocessing (EMDR session run on seven healthy volunteers. EMDR was applied on autobiographic worries causing moderate distress. The EMDR session was complete in 5 out of the 7 cases; distress measured by SUDS (Subjective Units of Discomfort Scale decreased to a near zero value. Smooth pursuit eye movements were recorded by an Eyelink II video system before and after EMDR. For the five complete sessions, pursuit eye movement improved after their EMDR session. Notably, the number of saccade intrusions-catch-up saccades (CUS-decreased and, reciprocally, there was an increase in the smooth components of the pursuit. Such an increase in the smoothness of the pursuit presumably reflects an improvement in the use of visual attention needed to follow the target accurately. Perhaps EMDR reduces distress thereby activating a cholinergic effect known to improve ocular pursuit.
Kahane, Leo H
2007-01-01
Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics. New to the Second Edition Offers greater coverage of simple panel-data estimation:
In pursuit of homoleptic actinide alkyl complexes.
Seaman, Lani A; Walensky, Justin R; Wu, Guang; Hayton, Trevor W
2013-04-01
This Forum Article describes the pursuit of isolable homoleptic actinide alkyl complexes, starting with the pioneering work of Gilman during the Manhattan project. The initial reports in this area suggested that homoleptic uranium alkyls were too unstable to be isolated, but Wilkinson demonstrated that tractable uranium alkyls could be generated by purposeful "ate" complex formation, which serves to saturate the uranium coordination sphere and provide the complexes with greater kinetic stability. More recently, we reported the solid-state molecular structures of several homoleptic uranium alkyl complexes, including [Li(THF)4][U(CH2(t)Bu)5], [Li(TMEDA)]2[UMe6], [K(THF)]3[K(THF)2][U(CH2Ph)6]2, and [Li(THF)4][U(CH2SiMe3)6], by employing Wilkinson's strategy. Herein, we describe our attempts to extend this chemistry to thorium. The treatment of ThCl4(DME)2 with 5 equiv of LiCH2(t)Bu or LiCH2SiMe3 at -25 °C in THF affords [Th(CH2(t)Bu)5] (1) and [Li(DME)2][Th(CH2SiMe3)5 (2), respectively, in moderate yields. Similarly, the treatment of ThCl4(DME)2 with 6 equiv of K(CH2Ph) produces [K(THF)]2[Th(CH2Ph)6] (3), in good yield. Complexes 1-3 have been fully characterized, while the structures of 1 and 3 were confirmed by X-ray crystallography. Additionally, the electronic properties of 1 and 3 were explored by density functional theory.
马峰; 王千; 蔺文静; 王贵玲
2012-01-01
石家庄市处于我国缺水严重的华北地区,水资源利用一直倍受人们的关注,水资源承载力评价可为今后的地区水资源利用及规划提供建议.文章采用了综合指标法,根据石家庄市水资源具体情况和指标体系结构特点,选取了18个指标建立水资源承载力评价指标体系及指标标准,运用投影寻踪方法建立评价模型,通过归一化处理、线性投影、构造投影指标函数和优化投影指标函数的方法,将选取的指标运用matlab数学软件进行投影寻踪分析,得到石家庄市水资源承载力等级水平为Ⅳ级,主要影响水资源承载力的指标为基本农田比例、节水灌溉率、灌溉用水有效利用系数、水资源可开发利用系数和万元工业增加值用水量等.%Shijiazhuang lies in the north of china which is seriously lack of water, and its water resources utilization always receives attention. The evaluation of water resources carrying capacity could provide advices for water resources utilization and planning in this area in future. Based on the specific conditions of water resources and the structural features of the index system in Shijiazhuang.18 indexes were selected to build the evaluation index system of water resources carrying capacity. The projection pursuit method was used to assess the model. Relying on the methods of normalization treatment, linear projection, constructing projection target function as well as optimizing projection target function, the selected indexes were analyzed using the projective pursuit method based on matlab platform. The results showed that the water resources carrying capacity level is grade IV in Shijiazhuang. The main indexes affecting the water resources carrying capacity included the basic farmland proportion, water-saving irrigation rate,effective utilization coefficient of irrigation water, utilization coefficient of available water resources, and water consumption of ten thousand yuan
Predictors of pursuit of physician-assisted death.
Smith, Kathryn A; Harvath, Theresa A; Goy, Elizabeth R; Ganzini, Linda
2015-03-01
Physician-assisted death (PAD) was legalized in 1997 by Oregon's Death with Dignity Act. The States of Washington, Montana, Vermont, and New Mexico have since provided legal sanction for PAD. Through 2013, 1173 Oregonians have received a prescription under the Death with Dignity Act and 752 have died after taking the prescribed medication in Oregon. To determine the predictive value of personal and interpersonal variables in the pursuit of PAD. Fifty-five Oregonians who either requested PAD or contacted a PAD advocacy organization were compared with 39 individuals with advanced disease who did not pursue PAD. We compared the two groups on responses to standardized measures of depression, hopelessness, spirituality, social support, and pain. We also compared the two groups on style of attachment to intimate others and caregivers as understood through attachment theory. We found that PAD requesters had higher levels of depression, hopelessness, and dismissive attachment (attachment to others characterized by independence and self-reliance), and lower levels of spirituality. There were moderate correlations among the variables of spirituality, hopelessness, depression, social support, and dismissive attachment. There was a strong correlation between depression and hopelessness. Low spirituality emerged as the strongest predictor of pursuit of PAD in the regression analysis. Although some factors motivating pursuit of PAD, such as depression, may be ameliorated by medical interventions, other factors, such as style of attachment and sense of spirituality, are long-standing aspects of the individual that should be supported at the end of life. Practitioners must develop respectful awareness and understanding of the interpersonal and spiritual perspectives of their patients to provide such support. Published by Elsevier Inc.
Matson, Johnny L.; Kozlowski, Alison M.
2010-01-01
Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…
Nick, Todd G; Campbell, Kathleen M
2007-01-01
The Medical Subject Headings (MeSH) thesaurus used by the National Library of Medicine defines logistic regression models as "statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable." Logistic regression models are used to study effects of predictor variables on categorical outcomes and normally the outcome is binary, such as presence or absence of disease (e.g., non-Hodgkin's lymphoma), in which case the model is called a binary logistic model. When there are multiple predictors (e.g., risk factors and treatments) the model is referred to as a multiple or multivariable logistic regression model and is one of the most frequently used statistical model in medical journals. In this chapter, we examine both simple and multiple binary logistic regression models and present related issues, including interaction, categorical predictor variables, continuous predictor variables, and goodness of fit.
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
In Pursuit of Land Tenure Security
Dekker, Henri
2006-01-01
In Pursuit of Land Tenure Security is a unique book that takes the reader on an international tour of perceptions of land tenure security. It contains an anthology of essays based on contacts with people during assignments in various parts of the world over a period of several years. The essays describe the human pursuit for a higher level of land tenure security. Because land tenure security is a perception, the use of stories of human experience introduces the reader to an array of issues a...
Constrained Sparse Galerkin Regression
Loiseau, Jean-Christophe
2016-01-01
In this work, we demonstrate the use of sparse regression techniques from machine learning to identify nonlinear low-order models of a fluid system purely from measurement data. In particular, we extend the sparse identification of nonlinear dynamics (SINDy) algorithm to enforce physical constraints in the regression, leading to energy conservation. The resulting models are closely related to Galerkin projection models, but the present method does not require the use of a full-order or high-fidelity Navier-Stokes solver to project onto basis modes. Instead, the most parsimonious nonlinear model is determined that is consistent with observed measurement data and satisfies necessary constraints. The constrained Galerkin regression algorithm is implemented on the fluid flow past a circular cylinder, demonstrating the ability to accurately construct models from data.
Amin, Mohd Zaki M.; Islam, Tanvir; Ishak, Asnor M.
2014-10-01
The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961-2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18-6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011-2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961-2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and
In Pursuit of Land Tenure Security
Dekker, Henri
2006-01-01
In Pursuit of Land Tenure Security is a unique book that takes the reader on an international tour of perceptions of land tenure security. It contains an anthology of essays based on contacts with people during assignments in various parts of the world over a period of several years. The essays desc
The Pursuit of Excellence through Education.
Ferrari, Michel, Ed.
In this book theorists and researchers present a range of perspectives on how to promote excellence in education, providing an opportunity for expression to those who stress transformation of educational practice and those who emphasize individual abilities. In part 1, The Individual Pursuit of Excellence, the chapters are: (1) Learning from…
Neurophysiology and Neuroanatomy of Smooth Pursuit in Humans
Lencer, Rebekka; Trillenberg, Peter
2008-01-01
Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved…
Independent histogram pursuit for segmentation of skin lesions
Gomez, D.D.; Butakoff, C.; Ersbøll, Bjarne Kjær;
2008-01-01
In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (HIP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first estima...... to deal with different types of dermatological lesions. The boundary detection precision using k-means segmentation was close to 97%. The proposed algorithm can be easily combined with the majority of classification algorithms.......In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (HIP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first...... estimated combination enhances the contrast of the lesion to facilitate its segmentation. Given an N-band image, this first combination corresponds to a line in N dimensions, such that the separation between the two main modes of the histogram obtained by projecting the pixels onto this line, is maximized...
Cursive writing with smooth pursuit eye movements.
Lorenceau, Jean
2012-08-21
The eyes never cease to move: ballistic saccades quickly turn the gaze toward peripheral targets, whereas smooth pursuit maintains moving targets on the fovea where visual acuity is best. Despite the oculomotor system being endowed with exquisite motor abilities, any attempt to generate smooth eye movements against a static background results in saccadic eye movements. Although exceptions to this rule have been reported, volitional control over smooth eye movements is at best rudimentary. Here, I introduce a novel, temporally modulated visual display, which, although static, sustains smooth eye movements in arbitrary directions. After brief training, participants gain volitional control over smooth pursuit eye movements and can generate digits, letters, words, or drawings at will. For persons deprived of limb movement, this offers a fast, creative, and personal means of linguistic and emotional expression. Copyright © 2012 Elsevier Ltd. All rights reserved.
Pursuit and Synchronization in Hydrodynamic Dipoles
Kanso, Eva
2015-01-01
We study theoretically the behavior of a class of hydrodynamic dipoles. This study is motivated by recent experiments on synthetic and biological swimmers in microfluidic \\textit{Hele-Shaw} type geometries. Under such confinement, a swimmer's hydrodynamic signature is that of a potential source dipole, and the long-range interactions among swimmers are obtained from the superposition of dipole singularities. Here, we recall the equations governing the positions and orientations of interacting asymmetric swimmers in doubly-periodic domains, and focus on the dynamics of swimmer pairs. We obtain two families of `relative equilibria'-type solutions that correspond to pursuit and synchronization of the two swimmers, respectively. Interestingly, the pursuit mode is stable for large tail swimmers whereas the synchronization mode is stable for large head swimmers. These results have profound implications on the collective behavior reported in several recent studies on populations of confined microswimmers.
Prey pursuit and interception in dragonflies.
Olberg, R M; Worthington, A H; Venator, K R
2000-02-01
Perching dragonflies (Libellulidae; Odonata) are sit-and-wait predators, which take off and pursue small flying insects. To investigate their prey pursuit strategy, we videotaped 36 prey-capture flights of male dragonflies, Erythemis simplicicollis and Leucorrhinia intacta, for frame-by-frame analysis. We found that dragonflies fly directly toward the point of prey interception by steering to minimize the movement of the prey's image on the retina. This behavior could be guided by target-selective descending interneurons which show directionally selective visual responses to small-object movement. We investigated how dragonflies discriminate distance of potential prey. We found a peak in angular velocity of the prey shortly before take-off which might cue the dragonfly to nearby flying targets. Parallax information from head movements was not required for successful prey pursuit.
Sharpen customer service skills with PCRAFT Pursuit.
Dologite, Kimberly A; Willner, Kathleen C; Klepeiss, Debra J; York, Susan A; Cericola, Lisa M
2003-01-01
Traditional approaches to teaching customer service skills do not involve participant interaction, nor do they provide a fun and relaxed atmosphere for learning. This article describes the development of PCRAFT Pursuit, an innovative game used to teach customer service skills. The development process began with concerns identified through patient satisfaction surveys. The implementation of this game became an integral component of education to improve customer service skills of staff throughout the hospital network.
Reframing our pursuit of life balance.
Fuentes, David G; Ogden, Rachel R; Ryan-Haddad, Ann; Strang, Aimee F
2015-04-25
During our time in the 2013 Academic Leadership Fellows Program, we explored what it takes to achieve life balance through a framework presented in a Harvard Business Review article. In this Statement, we describe 5 different areas from the article that provide infrastructure for reflecting on how we have learned to approach life balance in academia. We also provide brief messages based on this reading and others to help academics' pursuit of life balance.
Eeftens, M.R.; Beelen, R.M.J.; de Hoogh, K.; Bellander, T.; Cesaroni, G.; Cirach, M.; Declercq, C.; Dedele, A.; Dons, E.; de Nazelle, A.; Dimakopoulou, K.; Eriksen, K.; Falq, G.; Fischer, P.; Galassi, C.; Grazuleviciene, R.; Heinrich, J.; Hoffmann, B.; Jerrett, M.; Keidel, D.; Korek, M.; Lanki, T.; Lindley, S.; Madsen, C.; Molter, A.; Nador, G.; Nieuwenhuijsen, M.; Nonnemacher, M.; Pedeli, X.; Raaschou-Nielsen, O.; Patelarou, E.; Quass, U.; Ranzi, A.; Schindler, C.; Stempfelet, M.; Stephanou, E.; Sugiri, D.; Tsai, M.Y.; Yli-Tuomi, T.; Varro, M.J.; Vienneau, D.; von Klot, S.; van der Wolf, K.; Brunekreef, B.; Hoek, G.
2012-01-01
Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coar
Matching pursuit and source deflation for sparse EEG/MEG dipole moment estimation.
Wu, Shun Chi; Swindlehurst, A Lee
2013-08-01
In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole source localization and parameter estimation for multiple measurement vectors with constant sparsity. The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in estimation via alternating projections. The source-deflated matching pursuit (SDMP) approach mitigates the problem of residual interference inherent in sequential MP-based methods or recursively applied (RAP)-MUSIC. Furthermore, unlike prior methods based on alternating projection, SDMP allows one to efficiently estimate the dipole orientation in addition to its location. Simulations show that the proposed algorithms outperform existing techniques under various conditions, including those with highly correlated sources. Results using real EEG data from auditory experiments are also presented to illustrate the performance of these algorithms.
侯秀玲; 周益民; 王绍俊; 周密
2012-01-01
Soil heavy metals contamination has become one of the urgent problems faced by the development and internationalization of green food industry in China. Studies on these fields therefore are of great practical significance. This study emploies projection parameters to seek its projection direction, through projection index function to reflect the characteristics of soil heavy metals. This method possesses the advantages of objectivity and robust mathematical theoretical frameworks. More over, the subjective weight assignment might be avoided as a result. Soil samples from Toutun River area farmland were collected and tested as well based on the studied model to investigate the heavy metal distribution. The results show that chromium and vanadium present the dominant contaminants in studied areas, which display a decreasing tendency. Furthermore, it implies that the studied model can applicable in dealing with multiple factor problems, which can thus offer technical assistance in farmland soil heavy metal contaminants regulation.%重金属问题已成为我国开发绿色食品国际化过程中亟待解决的重要问题之一，对此问题展开研究具有重要的现实意义。通过将农田土壤重金属含量指标作为多个投影参数来寻求其投影方向，由投影指标函数来反映农田重金属含量的特征，避免了人为赋予权重的干扰，客观性强，数学概念清晰。利用投影寻踪模型分析了头屯河地区的农田土壤重金属污染的规律，结果表明头屯河农场土壤的重金属污染以铬和钒为主要污染因子，呈现逐渐减小的规律。应用结果表明，投影寻踪模型能够较好地处理多因素问题，为中国农田土壤污染治理和控制提供科学依据。
Kongsted, Alice; Jørgensen, Lars Vincents; Leboeuf-Yde, Charlotte
2008-01-01
-year follow-up. SETTING: The study was carried out at a university research centre and participants were recruited from emergency units and general practitioners. SUBJECTS: In all, 262 participants were recruited within 10 days from a whiplash injury. MAIN MEASURES: Smooth pursuit eye movements were tested......OBJECTIVE: To evaluate the ability of early smooth pursuit testing to predict chronic whiplash-associated disorders, and to study whether the presence of abnormal smooth pursuit eye movements at one-year follow-up is associated with symptoms at that time. DESIGN: Prospective cohort study with one...... collision were determined. RESULTS: Results of early eye movement tests were not associated with the prognosis. Reduced smooth pursuit performance when tested in static cervical rotation at the one-year follow-up was significantly associated with higher neck pain intensity at that time (regression...
Smooth pursuit eye movements and schizophrenia: literature review.
Franco, J G; de Pablo, J; Gaviria, A M; Sepúlveda, E; Vilella, E
2014-09-01
To review the scientific literature about the relationship between impairment on smooth pursuit eye movements and schizophrenia. Narrative review that includes historical articles, reports about basic and clinical investigation, systematic reviews, and meta-analysis on the topic. Up to 80% of schizophrenic patients have impairment of smooth pursuit eye movements. Despite the diversity of test protocols, 65% of patients and controls are correctly classified by their overall performance during this pursuit. The smooth pursuit eye movements depend on the ability to anticipate the target's velocity and the visual feedback, as well as on learning and attention. The neuroanatomy implicated in smooth pursuit overlaps to some extent with certain frontal cortex zones associated with some clinical and neuropsychological characteristics of the schizophrenia, therefore some specific components of smooth pursuit anomalies could serve as biomarkers of the disease. Due to their sedative effect, antipsychotics have a deleterious effect on smooth pursuit eye movements, thus these movements cannot be used to evaluate the efficacy of the currently available treatments. Standardized evaluation of smooth pursuit eye movements on schizophrenia will allow to use specific aspects of that pursuit as biomarkers for the study of its genetics, psychopathology, or neuropsychology. Copyright © 2013 Sociedad Española de Oftalmología. Published by Elsevier Espana. All rights reserved.
Neurophysiology and Neuroanatomy of Smooth Pursuit: Lesion Studies
Sharpe, James A.
2008-01-01
Smooth pursuit impairment is recognized clinically by the presence of saccadic tracking of a small object and quantified by reduction in pursuit gain, the ratio of smooth eye movement velocity to the velocity of a foveal target. Correlation of the site of brain lesions, identified by imaging or neuropathological examination, with defective smooth…
CF-Pursuit: A Pursuit Method with a Clothoid Fitting and a Fuzzy Controller for Autonomous Vehicles
Yunxiao Shan
2015-09-01
Full Text Available Simple and efficient geometric controllers, like Pure-Pursuit, have been widely used in various types of autonomous vehicles to solve tracking problems. In this paper, we have developed a new pursuit method, named CFPursuit, which has been based on Pure-Pursuit but with certain differences. In CF-Pursuit, in order to reduce fitting errors, we used a clothoid C1 curve to replace the circle employed in Pure-Pursuit. This improvement to the fitting method helps the Pursuit method to decrease tracking errors. As regards the selection of look-ahead distance, we employed a fuzzy system to directly consider the path’s curvature. There are three input variables in this fuzzy system, 6mcurvature, 9mcurvature and 12mcurvature, calculated from the clothoid fit with the current position and the goal position on the defined path. A Sugeno fuzzy model was adapted to output a reasonable look-ahead distance using the experiences of human drivers as well as our own tests. Compared with some other geometric controllers, CF-Pursuit performs better in robustness, cross track errors and stability. The results from field tests have proven the CF-Pursuit is a practical and efficient geometric method for the path tracking problems of autonomous vehicles.
Land, Kenneth C.; And Others
1994-01-01
Advantages of using logistic and hazards regression techniques in assessing the overall impact of a treatment program and the differential impact on client subgroups are examined and compared using data from a juvenile court program for status offenders. Implications are drawn for management and effectiveness of intensive supervision programs.…
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Melinder, Annika; Konijnenberg, Carolien; Sarfi, Monica
2013-12-01
Although an increasing number of children are born to mothers in opioid maintenance therapy (OMT), little is known about the long-term effects of these opioids. Previous studies suggest an association between prenatal OMT exposure and difficulties in eye movement control. Also, the effects of tobacco smoking on eye movements have been reported. The present study examined the influence of eye movements, i.e. smooth pursuit, on visuomotor capabilities in children of smoking mothers in OMT. The study comprised a 2 (OMT versus contrast group) × 2 (slow versus fast smooth pursuit) between-subject factorial design. The cognitive developmental research unit at the University of Oslo, Norway. Participants were 26 4-year-old children of tobacco-smoking women in OMT and 23 non-exposed 4-year-old children, with non-smoking mothers, matched by gender and age. Eye movements and smooth pursuit were recorded using a Tobii 1750 eyetracker. Visuomotor functions were examined by Bender test. The OMT group tracked slowly moving objects with smooth pursuit in a similar manner to their non-exposed peers. When fast smooth pursuit was measured, the OMT group of children tracked the object more slowly than the contrast group, P = 0.02, ηp(2) = 0.11. A regression analysis showed that fast smooth pursuit predicted children's performance on a visuomotor task, R(2) = 0.37. Impaired eye-tracking skills in 4-year-old children exposed to methadone or buprenorphine and tobacco prenatally could inhibit the development of some cognitive functions in later life. ©2013 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of The Society for the Study of Addiction.
The Pursuit of Identity in Invisible Man
谭佳
2013-01-01
Invisible Man is a representative work of black literature in America. In this novel, the writer Ralph Ellison depicts the hero’s growth experience in the white dominated society with his unique narrative techniques. As an individual in a society, the hero in this novel gradually realizes that he is an invisible man in the white dominated society and he doesn ’t have the social sta-tus which can be recognized by the white at all. To change this situation, the hero in this novel suffers many difficulties and hard-ships with an attempt to prove his existence in front of the white and the numerous black fellows and obtain his own identity as a black man which will be recognized by others. This paper tries to explore African American ’s pursuit of identity in Invisible Man by interpreting Ellison’s Invisible Man.
Principal Component Pursuit with Reduced Linear Measurements
Ganesh, Arvind; Wright, John; Ma, Yi
2012-01-01
In this paper, we study the problem of decomposing a superposition of a low-rank matrix and a sparse matrix when a relatively few linear measurements are available. This problem arises in many data processing tasks such as aligning multiple images or rectifying regular texture, where the goal is to recover a low-rank matrix with a large fraction of corrupted entries in the presence of nonlinear domain transformation. We consider a natural convex heuristic to this problem which is a variant to the recently proposed Principal Component Pursuit. We prove that under suitable conditions, this convex program guarantees to recover the correct low-rank and sparse components despite reduced measurements. Our analysis covers both random and deterministic measurement models.
John Hejduk's Pursuit of an Architectural Ethos
Søberg, Martin
2012-01-01
of architectural drawing; a method which, when approached on a more general and conceptual level, might even have the potential to inform design-based architectural research today. The author argues that the conceptual framework of such a method is not a theoretical pursuit of logos, but more a matter of character......Reflected, artistic practices and design-based research are drastically expanding fields within architectural academia. However, the interest in uniting theory and practice is not entirely new. Just a few decades ago, before a ‘death of theory’ was proclaimed, questions of architectural...... epistemology, of the language(s) of architecture, were indeed of profound interest to the discipline. This essay returns to and examines the investigatory practices of John Hejduk in an attempt to identify a poetic method asserting difference through repetition and primarily grounded in the medium...
Multiparameter image visualization by projection pursuit (Proceedings Only)
Harikumar, G.; Bresler, Yoram
1992-09-01
This paper addresses the display of multi-parameter medical image data, such as arises in MRI or multimodality image fusion. MRI or multi modality studies produce several different images of a given cross-section of the body, each providing different levels of contrast sensitivity between different tissues. The question then arises as to how to present this wealth of data to the diagnostician. While each of the different images may be misleading (as illustrated later by an example), in combination they may contain the correct information. Unfortunately, a human observer is not likely to be able to extract this information when presented with a parallel display of the distinct images. Given the sequential nature of detailed visual examination of a picture, a human observer is quite ineffective at integrating complex visual data from parallel sources. The development of a display technology that overcomes this difficulty by synthesizing a display method matched to the capabilities of the human observer is the subject of this paper. The ultimate goal of diagnostic imaging is the detection, localization, and quantification of abnormality. An intermediate goal, which is the one we address, is to present the diagnostician with an image that will maximize his changes to classify correctly different regions in the image as belonging to different tissue types. Our premise is that the diagnostician is able to bring to bear all his knowledge and experience, which are difficult to capture in a computer program, on the final analysis process. This is often key to the detection of subtle and otherwise elusive features in the image. We therefore rule out the generation of an automatically segmented image, which not only fails to include this knowledge, but also would deprive the diagnostician of the opportunity to exercise it, by presenting him with a hard-labeled segmentation. Instead we concentrate on the fusion of the multiple images of the same cross-section into a single most informative grey-scale image.
Project Based Learning: In Pursuit of Androgogic Effectiveness
Ntombela, Berrington X. S.
2015-01-01
In an attempt to standardise Foundation Programmes for Oman higher education providers, the Oman Academic Standards for General Foundation Programmes stipulated that higher education providers should offer programmes that ensure androgogic effectiveness. In the light of that, this paper presents attempts by a University College in Oman to…
Hofmann, Wilhelm; Finkel, Eli J; Fitzsimons, Gráinne M
2015-09-01
In the new millennium, scholars have built a robust intersection between close-relationships research and self-regulation research. However, virtually no work has investigated how the most basic and broad indicator of relationship quality, relationship satisfaction, affects self-regulation and vice versa. In the present research, we show that higher relationship satisfaction promotes a motivational mind-set that is conducive for effective self-regulation, and thus for goal progress and performance. In Study 1-a large-scale, intensive experience sampling project of 115 couples (total N = 230)-we closely tracked fluctuations in state relationship satisfaction (SRS) and 4 parameters of effective self-regulation according to our conceptual model. Dyadic process analyses showed that individuals experiencing higher SRS than they typically do exhibited higher levels of (a) perceived control, (b) goal focus, (c) perceived partner support, and (d) positive affect during goal pursuit than they typically exhibit. Together, these 4 self-regulation-relevant variables translated into higher rates of daily progress on specific, idiographic goals. In Study 2 (N = 195), we employed a novel experimental manipulation of SRS, replicating the link between SRS and parameters of effective self-regulation. Taken together, these findings suggest that momentary increases in relationship satisfaction may benefit everyday goal pursuit through a combination of cognitive and affective mechanisms, thus further integrating relationship research with social-cognitive research on goal pursuit. (c) 2015 APA, all rights reserved).
Regression analysis by example
Chatterjee, Samprit; Hadi, Ali S
2012-01-01
.... The emphasis continues to be on exploratory data analysis rather than statistical theory. The coverage offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression...
Liability for Damage Caused at the Pursuit of Financial Advisory
Slezáková Andrea
2017-06-01
Full Text Available The Act No 186/2009 Coll. on financial intermediation and financial advisory and on amendments and supplements to certain laws is reflecting on the topic of liability. It is incorporating provisions about the liability for damage at the pursuit of financial advisory. The attention is being paid to the liability for damage caused to the professional or non-professional client at the pursuit of financial advisory. In accordance with the element of the liability legal relationship, the subjective aspect, the liability for damage caused at the pursuit of financial advisory represents a subjective liability, where fault is necessary. Our proposal de lege ferenda is the introduction of strict liability for damage caused at the pursuit of financial advisory.
Bakst, Leah; Fleuriet, Jérome; Mustari, Michael J
2017-05-01
Neurons in the smooth eye movement subregion of the frontal eye field (FEFsem) are known to play an important role in voluntary smooth pursuit eye movements. Underlying this function are projections to parietal and prefrontal visual association areas and subcortical structures, all known to play vital but differing roles in the execution of smooth pursuit. Additionally, the FEFsem has been shown to carry a diverse array of signals (e.g., eye velocity, acceleration, gain control). We hypothesized that distinct subpopulations of FEFsem neurons subserve these diverse functions and projections, and that the relative weights of retinal and extraretinal signals could form the basis for categorization of units. To investigate this, we used a step-ramp tracking task with a target blink to determine the relative contributions of retinal and extraretinal signals in individual FEFsem neurons throughout pursuit. We found that the contributions of retinal and extraretinal signals to neuronal activity and behavior change throughout the time course of pursuit. A clustering algorithm revealed three distinct neuronal subpopulations: cluster 1 was defined by a higher sensitivity to eye velocity, acceleration, and retinal image motion; cluster 2 had greater activity during blinks; and cluster 3 had significantly greater eye position sensitivity. We also performed a comparison with a sample of medial superior temporal neurons to assess similarities and differences between the two areas. Our results indicate the utility of simple tests such as the target blink for parsing the complex and multifaceted roles of cortical areas in behavior.NEW & NOTEWORTHY The frontal eye field (FEF) is known to play a critical role in volitional smooth pursuit, carrying a variety of signals that are distributed throughout the brain. This study used a novel application of a target blink task during step ramp tracking to determine, in combination with a clustering algorithm, the relative contributions of
Johansen, Søren
2008-01-01
The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating e...
Ito, Norie; Takei, Hidetoshi; Chiba, Susumu; Inoue, Kiyoharu; Fukushima, Kikuro
2016-01-01
Although impaired smooth-pursuit in Parkinson's disease (PD) is well known, reports are conflicting on the ability to cancel vestibulo-ocular reflex (VOR) when the target moves with head, requiring gaze-pursuit. To compare visual tracking performance with or without passive whole-body rotation, we examined eye movements of 10 PD patients and 6 age-matched controls during sinusoidal horizontal smooth-pursuit and passive whole-body rotation (0.3 Hz, ± 10°). Three tasks were tested: smooth-pursuit, VOR cancellation, and VORx1 while subjects fixated an earth-stationary spot during whole-body rotation. Mean ± SD eye velocity gains (eye velocities/stimulus velocities) of PD patients during the 3 tasks were 0.32 ± 0.24 0.25 ± 0.22, 0.85 ± 0.20, whereas those of controls were 0.91 ± 0.06, 0.14 ± 0.07, 0.94 ± 0.05, respectively. Difference was significant between the two subject groups only during smooth-pursuit. Plotting eye-velocity gains of individual subjects during VOR cancellation against those during smooth-pursuit revealed significant negative linear correlation between the two parameters in the controls, but no correlation was found in PD patients. Based on the regression equation of the controls, we estimated expected eye velocity gains of individual subjects during VOR cancellation from their smooth-pursuit gains. Estimated gains of PD patients during VOR cancellation were significantly different from their actual gains, suggesting that different neural mechanisms operate during VOR cancellation in the controls and PD.
The Initiation of Smooth Pursuit is Delayed in Anisometropic Amblyopia.
Raashid, Rana Arham; Liu, Ivy Ziqian; Blakeman, Alan; Goltz, Herbert C; Wong, Agnes M F
2016-04-01
Several behavioral studies have shown that the reaction times of visually guided movements are slower in people with amblyopia, particularly during amblyopic eye viewing. Here, we tested the hypothesis that the initiation of smooth pursuit eye movements, which are responsible for accurately keeping moving objects on the fovea, is delayed in people with anisometropic amblyopia. Eleven participants with anisometropic amblyopia and 14 visually normal observers were asked to track a step-ramp target moving at ±15°/s horizontally as quickly and as accurately as possible. The experiment was conducted under three viewing conditions: amblyopic/nondominant eye, binocular, and fellow/dominant eye viewing. Outcome measures were smooth pursuit latency, open-loop gain, steady state gain, and catch-up saccade frequency. Participants with anisometropic amblyopia initiated smooth pursuit significantly slower during amblyopic eye viewing (206 ± 20 ms) than visually normal observers viewing with their nondominant eye (183 ± 17 ms, P = 0.002). However, mean pursuit latency in the anisometropic amblyopia group during binocular and monocular fellow eye viewing was comparable to the visually normal group. Mean open-loop gain, steady state gain, and catch-up saccade frequency were similar between the two groups, but participants with anisometropic amblyopia exhibited more variable steady state gain (P = 0.045). This study provides evidence of temporally delayed smooth pursuit initiation in anisometropic amblyopia. After initiation, the smooth pursuit velocity profile in anisometropic amblyopia participants is similar to visually normal controls. This finding differs from what has been observed previously in participants with strabismic amblyopia who exhibit reduced smooth pursuit velocity gains with more catch-up saccades.
Experimental and computational analysis of monkey smooth pursuit eye movements.
Churchland, M M; Lisberger, S G
2001-08-01
Smooth pursuit eye movements are guided by visual feedback and are surprisingly accurate despite the time delay between visual input and motor output. Previous models have reproduced the accuracy of pursuit either by using elaborate visual signals or by adding sources of motor feedback. Our goal was to constrain what types of signals drive pursuit by obtaining data that would discriminate between these two modeling approaches, represented by the "image motion model" and the "tachometer feedback" model. Our first set of experiments probed the visual properties of pursuit with brief square-pulse and sine-wave perturbations of target velocity. Responses to pulse perturbations increased almost linearly with pulse amplitude, while responses to sine wave perturbations showed strong saturation with increasing stimulus amplitude. The response to sine wave perturbations was strongly dependent on the baseline image velocity at the time of the perturbation. Responses were much smaller if baseline image velocity was naturally large, or was artificially increased by superimposing sine waves on pulse perturbations. The image motion model, but not the tachometer feedback model, could reproduce these features of pursuit. We used a revision of the image motion model that was, like the original, sensitive to both image velocity and image acceleration. Due to a saturating nonlinearity, the sensitivity to image acceleration declined with increasing image velocity. Inclusion of this nonlinearity was motivated by our experimental results, was critical in accounting for the responses to perturbations, and provided an explanation for the unexpected stability of pursuit in the presence of perturbations near the resonant frequency. As an emergent property, the revised image motion model was able to reproduce the frequency and damping of oscillations recorded during artificial feedback delays. Our second set of experiments replicated prior recordings of pursuit responses to multiple
Context-specific adaptation of pursuit initiation in humans
Takagi, M.; Abe, H.; Hasegawa, S.; Usui, T.; Hasebe, H.; Miki, A.; Zee, D. S.; Shelhauser, M. (Principal Investigator)
2000-01-01
PURPOSE: To determine if multiple states for the initiation of pursuit, as assessed by acceleration in the "open-loop" period, can be learned and gated by context. METHODS: Four normal subjects were studied. A modified step-ramp paradigm for horizontal pursuit was used to induce adaptation. In an increasing paradigm, target velocity doubled 230 msec after onset; in a decreasing paradigm, it was halved. In the first experiment, vertical eye position (+/-5 degrees ) was used as the context cue, and the training paradigm (increasing or decreasing) changed with vertical eye position. In the second experiment, with vertical position constant, when the target was red, training was decreasing, and when green, increasing. The average eye acceleration in the first 100 msec of tracking was the index of open-loop pursuit performance. RESULTS: With vertical position as the cue, pursuit adaptation differed between up and down gaze. In some cases, the direction of adaptation was in exact accord with the training stimuli. In others, acceleration increased or decreased for both up and down gaze but always in correct relative proportion to the training stimuli. In contrast, multiple adaptive states were not induced with color as the cue. CONCLUSIONS: Multiple values for the relationship between the average eye acceleration during the initiation of pursuit and target velocity could be learned and gated by context. Vertical position was an effective contextual cue but not target color, implying that useful contextual cues must be similar to those occurring naturally, for example, orbital position with eye muscle weakness.
Regression analysis by example
Chatterjee, Samprit
2012-01-01
Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded
Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems
Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung
2015-01-01
The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...
Unitary Response Regression Models
Lipovetsky, S.
2007-01-01
The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…
Flexible survival regression modelling
Cortese, Giuliana; Scheike, Thomas H; Martinussen, Torben
2009-01-01
Regression analysis of survival data, and more generally event history data, is typically based on Cox's regression model. We here review some recent methodology, focusing on the limitations of Cox's regression model. The key limitation is that the model is not well suited to represent time-varyi...
Fitzenberger, Bernd; Wilke, Ralf Andreas
2015-01-01
Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights by m...... treatment of the topic is based on the perspective of applied researchers using quantile regression in their empirical work....
Automatic Epileptic Seizure Onset Detection Using Matching Pursuit
Sorensen, Thomas Lynggaard; Olsen, Ulrich L.; Conradsen, Isa
2010-01-01
An automatic alarm system for detecting epileptic seizure onsets could be of great assistance to patients and medical staff. A novel approach is proposed using the Matching Pursuit algorithm as a feature extractor combined with the Support Vector Machine (SVM) as a classifier for this purpose....... The combination of Matching Pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial...... electroencephalography (iEEG). A sensitivity of 78-100% and a detection latency of 5-18s has been achieved, while holding the false detection at 0.16-5.31/h. Our results show the potential of Matching Pursuit as a feature xtractor for detection of epileptic seizures....
Relative Effects of Forward and Backward Planning on Goal Pursuit.
Park, Jooyoung; Lu, Fang-Chi; Hedgcock, William M
2017-09-01
Considerable research has shown that planning plays an important role in goal pursuit. But how does the way people plan affect goal pursuit? Research on this question is scarce. In the current research, we examined how planning the steps required for goal attainment in chronological order (i.e., forward planning) and reverse chronological order (i.e., backward planning) influences individuals' motivation for and perceptions of goal pursuit. Compared with forward planning, backward planning not only led to greater motivation, higher goal expectancy, and less time pressure but also resulted in better goal-relevant performance. We further demonstrated that this motivational effect occurred because backward planning allowed people to think of tasks required to reach their goals more clearly, especially when goals were complex to plan. These findings suggest that the way people plan matters just as much as whether or not they plan.
Naghshpour, Shahdad
2012-01-01
Regression analysis is the most commonly used statistical method in the world. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation and will help demystify regression analysis using examples from economics and with real data to show the applications of the method. T
YAMPA: Yet Another Matching Pursuit Algorithm for compressive sensing
Lodhi, Muhammad A.; Voronin, Sergey; Bajwa, Waheed U.
2016-05-01
State-of-the-art sparse recovery methods often rely on the restricted isometry property for their theoretical guarantees. However, they cannot explicitly incorporate metrics such as restricted isometry constants within their recovery procedures due to the computational intractability of calculating such metrics. This paper formulates an iterative algorithm, termed yet another matching pursuit algorithm (YAMPA), for recovery of sparse signals from compressive measurements. YAMPA differs from other pursuit algorithms in that: (i) it adapts to the measurement matrix using a threshold that is explicitly dependent on two computable coherence metrics of the matrix, and (ii) it does not require knowledge of the signal sparsity. Performance comparisons of YAMPA against other matching pursuit and approximate message passing algorithms are made for several types of measurement matrices. These results show that while state-of-the-art approximate message passing algorithms outperform other algorithms (including YAMPA) in the case of well-conditioned random matrices, they completely break down in the case of ill-conditioned measurement matrices. On the other hand, YAMPA and comparable pursuit algorithms not only result in reasonable performance for well-conditioned matrices, but their performance also degrades gracefully for ill-conditioned matrices. The paper also shows that YAMPA uniformly outperforms other pursuit algorithms for the case of thresholding parameters chosen in a clairvoyant fashion. Further, when combined with a simple and fast technique for selecting thresholding parameters in the case of ill-conditioned matrices, YAMPA outperforms other pursuit algorithms in the regime of low undersampling, although some of these algorithms can outperform YAMPA in the regime of high undersampling in this setting.
Vectors, a tool in statistical regression theory
Corsten, L.C.A.
1958-01-01
Using linear algebra this thesis developed linear regression analysis including analysis of variance, covariance analysis, special experimental designs, linear and fertility adjustments, analysis of experiments at different places and times. The determination of the orthogonal projection, yielding e
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation...... error than existing greedy iterative descent methods such as matching pursuit (MP), and are competitive with models found using orthogonal MP (OMP), and orthogonal least squares (OLS). This implies that CMP is a strong alternative to the more computationally complex approaches of OMP and OLS...... for modeling high-dimensional signals....
Evolving Pacing Strategies for Team Pursuit Track Cycling
Wagner, Markus; Jordan, Diora; Kroeger, Trent; Neumann, Frank
2011-01-01
Team pursuit track cycling is a bicycle racing sport held on velodromes and is part of the Summer Olympics. It involves the use of strategies to minimize the overall time that a team of cyclists needs to complete a race. We present an optimisation framework for team pursuit track cycling and show how to evolve strategies using metaheuristics for this interesting real-world problem. Our experimental results show that these heuristics lead to significantly better strategies than state-of-art strategies that are currently used by teams of cyclists.
Chases and escapes the mathematics of pursuit and evasion
Nahin, Paul J
2012-01-01
We all played tag when we were kids. What most of us don't realize is that this simple chase game is in fact an application of pursuit theory, and that the same principles of games like tag, dodgeball, and hide-and-seek are also at play in military strategy, high-seas chases by the Coast Guard, and even romantic pursuits. In Chases and Escapes, Paul Nahin gives us the first complete history of this fascinating area of mathematics, from its classical analytical beginnings to the present day. Drawing on game theory, geometry, linear algebra, target-tracking algorithms, and much
DOPPLERLET BASED TIME-FREQUENCY REPRESENTATION VIA MATCHING PURSUITS
Zou Hongxing; Zhou Xiaobo; Dai Qionghai; Li Yanda
2001-01-01
A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fourier transform (including Gabor transform), wavelet transform, and chirplet transform are formulated in one framework of Dopplerlet transform accordingly.It is proved that the matching pursuits based on Dopplerlet basis functions are convergent, and that the energy of residual signals yielded in the decomposition process decays exponentially. Simulation results show that the matching pursuits with Dopplerlet basis functions can characterize compactly a nonstationary signal.
Autistic epileptiform regression.
Canitano, Roberto; Zappella, Michele
2006-01-01
Autistic regression is a well known condition that occurs in one third of children with pervasive developmental disorders, who, after normal development in the first year of life, undergo a global regression during the second year that encompasses language, social skills and play. In a portion of these subjects, epileptiform abnormalities are present with or without seizures, resembling, in some respects, other epileptiform regressions of language and behaviour such as Landau-Kleffner syndrome. In these cases, for a more accurate definition of the clinical entity, the term autistic epileptifom regression has been suggested. As in other epileptic syndromes with regression, the relationships between EEG abnormalities, language and behaviour, in autism, are still unclear. We describe two cases of autistic epileptiform regression selected from a larger group of children with autistic spectrum disorders, with the aim of discussing the clinical features of the condition, the therapeutic approach and the outcome.
Scaled Sparse Linear Regression
Sun, Tingni
2011-01-01
Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the noise level via the mean residual squares and scaling the penalty in proportion to the estimated noise level. The iterative algorithm costs nearly nothing beyond the computation of a path of the sparse regression estimator for penalty levels above a threshold. For the scaled Lasso, the algorithm is a gradient descent in a convex minimization of a penalized joint loss function for the regression coefficients and noise level. Under mild regularity conditions, we prove that the method yields simultaneously an estimator for the noise level and an estimated coefficient vector in the Lasso path satisfying certain oracle inequalities for the estimation of the noise level, prediction, and the estimation of regression coefficients. These oracle inequalities provide sufficient conditions for the consistency and asymptotic...
Rolling Regressions with Stata
Kit Baum
2004-01-01
This talk will describe some work underway to add a "rolling regression" capability to Stata's suite of time series features. Although commands such as "statsby" permit analysis of non-overlapping subsamples in the time domain, they are not suited to the analysis of overlapping (e.g. "moving window") samples. Both moving-window and widening-window techniques are often used to judge the stability of time series regression relationships. We will present an implementation of a rolling regression...
Guijun YANG; Lu LIN; Runchu ZHANG
2007-01-01
Quasi-regression, motivated by the problems arising in the computer experiments, focuses mainly on speeding up evaluation. However, its theoretical properties are unexplored systemically. This paper shows that quasi-regression is unbiased, strong convergent and asymptotic normal for parameter estimations but it is biased for the fitting of curve. Furthermore, a new method called unbiased quasi-regression is proposed. In addition to retaining the above asymptotic behaviors of parameter estimations, unbiased quasi-regression is unbiased for the fitting of curve.
Introduction to regression graphics
Cook, R Dennis
2009-01-01
Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava
Weisberg, Sanford
2005-01-01
Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: ""I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression."" -Technometrics, February 1987 ""Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis."" -American Scientist, May-June 1987
38 CFR 21.7654 - Pursuit and absences.
2010-07-01
...) VOCATIONAL REHABILITATION AND EDUCATION Educational Assistance for Members of the Selected Reserve Pursuit of...) Exceptions to the monthly verification requirement. A reservist does not have to submit a monthly... termination of training; (iii) Except as provided in § 21.7656(a), changes in the number of credit hours or in...
The Pursuit of Happiness, Stress and Temporomandibular Disorders
D. Marcus
2013-11-01
Full Text Available Mismanaging the pursuit of happiness causes negative psychological effects such as stress and disappointment. The resultant stress often manifests itself as psychological and physical health problems. We explore the problems of measuring happiness according to materialistic wealth and demonstrate that misinterpreting happiness can lead to a stress inducing pursuit. The happiness that human beings pursue is often material-based hedonism whereas eudaimonic happiness has been shown to be a by-product of the pursuit of meaningful activities. Pursuing a predefined happiness, the failure to achieve it and the resistance to it can create stress induced psychosomatic health problems; temporomandibular disorders (TMD are one such example. Masticatory myofascial pain syndrome is a form of TMD that has a strong association to psychological stress. In this paper the research on TMD associated facial pain across different socioeconomic status (SES groups is utilized to compare an objective, stress related physiological disorder with happiness data. We also discuss how the pressures of pursuing socially determined aesthetic happiness such as conforming to society’s expectations of smile and facial aesthetics can drive people to make surgical or orthodontic changes. This review proposes that pursuing happiness has the propensity to cause not only psychological stress but also negative behaviors. We aim to encourage further scientific research that will help to clarify this philosophical pursuit.
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximati...
Measuring Experiences of Interest-Related Pursuits in Connected Learning
Maul, Andrew; Penuel, William R.; Dadey, Nathan; Gallagher, Lawrence P.; Podkul, Timothy; Price, Emily
2017-01-01
This paper describes an effort to develop a survey instrument capable of measuring important aspects of adolescents' experiences of interest-related pursuits that are supported by technology. The measure focuses on youths' experiences of "connected learning" (Ito et al. in Connected learning: an agenda for research and design. Digital…
Incremental principal component pursuit for video background modeling
Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt
2017-03-14
An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.
Multi-target pursuit formation of multi-agent systems
Yan Jing; Guan Xin-Ping; Luo Xiao-Yuan
2011-01-01
The main goal of this paper is to design a team of agents that can accomplish multi-target pursuit formation using a developed leader-follower strategy. It is supposed that every target can accept a certain number of agents. First, each agent can automatically choose its target based on the distance from the agent to the target and the number of agents
Narcissism and the Strategic Pursuit of Short-Term Mating
Schmitt, David P.; Alcalay, Lidia; Allik, Jüri
2017-01-01
associating with key sexual outcomes (e.g., more active pursuit of short-term mating, intimate partner violence, and sexual aggression) and sex-related personality traits (e.g., higher extraversion and openness to experience). Whereas some features of personality (e.g., subjective well-being) were universally...
Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit
Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan
2012-01-01
We study packetized predictive control, known to be robust against packet dropouts in networked systems. To obtain sparse packets for rate-limited networks, we design control packets via an ℓ0 optimization, which can be eectively solved by orthogonal matching pursuit. Our formulation ensures asym...
The Selfish Goal: Unintended Consequences of Intended Goal Pursuits.
Bargh, John A; Green, Michelle; Fitzsimons, Gráinne
2008-10-01
Three experiments tested the hypothesis that consciously intended goal pursuits have unintended consequences for social judgment and behavior. From evolutionary theory (Dawkins 1976/2006) and empirical evidence of a nonconscious mode of goal pursuit (Bargh, 2005) we derive the hypothesis that most human goal pursuits are open-ended in nature: Once active, goals will operate on goal-relevant content in the environment, even if that content is not the intended focus of the conscious goal. Experiments 1 and 2 demonstrate that goals to evaluate a job applicant for either a waiter or crime reporter position also shape impressions of incidental bystanders in the situation, such that the bystander is later liked or disliked not on his own merits, but on how well his behavior matches the criteria consciously applied in evaluating the job applicant. Experiment 3 finds that a goal to help a specific target person spills over to influence actions toward incidental bystanders, but only while active. Implications of these findings for goal pursuit in everyday life are discussed.
Nieuport-Delage Pursuit Airplane 48 C. 1. : "jockey" type
1927-01-01
This is a light single-seat pursuit airplane with a tractor propeller actuated by a 12 cylinder V-type Hispano-Suiza engine giving 400 HP at 2000 R.P.M. This is a single winged aircraft capable of 273 km/h.
Positive affect as informational feedback in goal pursuit
Orehek, Edward; Bessarabova, Elena; Chen, Xiaoyan; Kruglanski, Arie W.
2011-01-01
Two studies investigated the cognitive activation of a goal following a promise to complete it. Current theorizing about the impact of positive affect as informational feedback in goal pursuit suggests two contradictory conclusions: (1) positive affect can signal that sufficient progress towards a g
Is the Study of Happiness a Worthy Scientific Pursuit?
Norrish, Jacolyn M.; Vella-Brodrick, Dianne A.
2008-01-01
This paper critiques the view that the study of happiness is not a worthy scientific pursuit. The happiness set point and hedonic treadmill theories denote the complexity of increasing happiness levels due to genetic limitations and adaptation, however, there is mounting evidence to suggest that with the use of appropriate measures and specific…
Rapid Nonconjugate Adaptation of Vertical Voluntary Pursuit Eye Movements
1991-01-01
applied to the post-adaptation data from the left eye magnification condition: YRpost(Transformed) = (2 * YRpre) - YRPost (6) For example, if the pie ...nonconjugate adaptation with spectacle- mounted plano -cylindrical lenses, Lemij (1990) demonstrated that nonconjugate pursuit adaptation was
Sense of place in outdoor-pursuits trip groups
Sharon L. Todd; Anderson B. Young; Lynn S. Anderson; Timothy S. O' Connell; Mary Breunig
2009-01-01
Studies have revealed that sense of community and group cohesion increase significantly over time in outdoor-pursuits trip groups. This study sought to understand similar development of sense of place. Do people simultaneously become more attached to or dependent on the natural environment as they grow closer to each other? Results from a study of college students...
Smooth pursuit eye movements improve temporal resolution for color perception.
Masahiko Terao
Full Text Available Human observers see a single mixed color (yellow when different colors (red and green rapidly alternate. Accumulating evidence suggests that the critical temporal frequency beyond which chromatic fusion occurs does not simply reflect the temporal limit of peripheral encoding. However, it remains poorly understood how the central processing controls the fusion frequency. Here we show that the fusion frequency can be elevated by extra-retinal signals during smooth pursuit. This eye movement can keep the image of a moving target in the fovea, but it also introduces a backward retinal sweep of the stationary background pattern. We found that the fusion frequency was higher when retinal color changes were generated by pursuit-induced background motions than when the same retinal color changes were generated by object motions during eye fixation. This temporal improvement cannot be ascribed to a general increase in contrast gain of specific neural mechanisms during pursuit, since the improvement was not observed with a pattern flickering without changing position on the retina or with a pattern moving in the direction opposite to the background motion during pursuit. Our findings indicate that chromatic fusion is controlled by a cortical mechanism that suppresses motion blur. A plausible mechanism is that eye-movement signals change spatiotemporal trajectories along which color signals are integrated so as to reduce chromatic integration at the same locations (i.e., along stationary trajectories on the retina that normally causes retinal blur during fixation.
Influence of positive subliminal and supraliminal affective cues on goal pursuit in schizophrenia
Chaillou, Anne Clémence; Giersch, Anne; Bonnefond, Anne; Custers, Ruud; Capa, Rémi L.
2015-01-01
Goal pursuit is known to be impaired in schizophrenia, but nothing much is known in these patients about unconscious affective processes underlying goal pursuit. Evidence suggests that in healthy individuals positive subliminal cues are taken as a signal that goal pursuit is easy and therefore reduc
38 CFR 21.310 - Rate of pursuit of a rehabilitation program.
2010-07-01
... rehabilitation program. 21.310 Section 21.310 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS... 38 U.S.C. Chapter 31 Rate of Pursuit § 21.310 Rate of pursuit of a rehabilitation program. (a... and part-time rate of pursuit of a rehabilitation program by a veteran whose ability to pursue...
The Neural Basis of Smooth Pursuit Eye Movements in the Rhesus Monkey Brain
Ilg, Uwe J.; Thier, Peter
2008-01-01
Smooth pursuit eye movements are performed in order to prevent retinal image blur of a moving object. Rhesus monkeys are able to perform smooth pursuit eye movements quite similar as humans, even if the pursuit target does not consist in a simple moving dot. Therefore, the study of the neuronal responses as well as the consequences of…
Multiagent pursuit-evasion games: Algorithms and experiments
Kim, Hyounjin
Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such
Gerber, Samuel [Univ. of Utah, Salt Lake City, UT (United States); Rubel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bremer, Peer -Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Whitaker, Ross T. [Univ. of Utah, Salt Lake City, UT (United States)
2012-01-19
This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduces a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse–Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this article introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to overfitting. The Morse–Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse–Smale regression. Supplementary Materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse–Smale complex approximation, and additional tables for the climate-simulation study.
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...
Quantile Regression With Measurement Error
Wei, Ying
2009-08-27
Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.
Matthias Schmid
Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.
Regression Benchmarking: An Approach to Quality Assurance in Performance
2005-01-01
The paper presents a short summary of our work in the area of regression benchmarking and its application to software development. Specially, we explain the concept of regression benchmarking, the requirements for employing regression testing in a software project, and methods used for analyzing the vast amounts of data resulting from repeated benchmarking. We present the application of regression benchmarking on a real software project and conclude with a glimpse at the challenges for the fu...
Hosmer, David W; Sturdivant, Rodney X
2013-01-01
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-
Weisberg, Sanford
2013-01-01
Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus
Transductive Ordinal Regression
Seah, Chun-Wei; Ong, Yew-Soon
2011-01-01
Ordinal regression is commonly formulated as a multi-class problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with the number of classes involved, due to the large number of labeled patterns that are needed. The availability of ordinal class labels, however, are often costly to calibrate or difficult to obtain. Unlabeled patterns, on the other hand, often exist in much greater abundance and are freely available. To take benefits from the abundance of unlabeled patterns, we present a novel transductive learning paradigm for ordinal regression in this paper, namely Transductive Ordinal Regression (TOR). The key challenge of the present study lies in the precise estimation of both the ordinal class label of the unlabeled data and the decision functions of the ordinal classes, simultaneously. The core elements of the proposed TOR include an objective function that caters to several commonly used loss functions casted in transductive setting...
Nonparametric Predictive Regression
Ioannis Kasparis; Elena Andreou; Phillips, Peter C.B.
2012-01-01
A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are proposed. The test statistics are related to those of Kasparis and Phillips (2012) and are obtained by kernel regression. The limit distribution of these predictive tests holds for a wide range of predictors including stationary as well as non-stationary fractional and near unit...
Landmine detection using two-tapped joint orthogonal matching pursuits
Goldberg, Sean; Glenn, Taylor; Wilson, Joseph N.; Gader, Paul D.
2012-06-01
Joint Orthogonal Matching Pursuits (JOMP) is used here in the context of landmine detection using data obtained from an electromagnetic induction (EMI) sensor. The response from an object containing metal can be decomposed into a discrete spectrum of relaxation frequencies (DSRF) from which we construct a dictionary. A greedy iterative algorithm is proposed for computing successive residuals of a signal by subtracting away the highest matching dictionary element at each step. The nal condence of a particular signal is a combination of the reciprocal of this residual and the mean of the complex component. A two-tap approach comparing signals on opposite sides of the geometric location of the sensor is examined and found to produce better classication. It is found that using only a single pursuit does a comparable job, reducing complexity and allowing for real-time implementation in automated target recognition systems. JOMP is particularly highlighted in comparison with a previous EMI detection algorithm known as String Match.
First-order optimality condition of basis pursuit denoise problem
朱玮; 舒适; 成礼智
2014-01-01
A new first-order optimality condition for the basis pursuit denoise (BPDN) problem is derived. This condition provides a new approach to choose the penalty param-eters adaptively for a fixed point iteration algorithm. Meanwhile, the result is extended to matrix completion which is a new field on the heel of the compressed sensing. The numerical experiments of sparse vector recovery and low-rank matrix completion show validity of the theoretic results.
Sparse Signals Recovery from Noisy Measurements by Orthogonal Matching Pursuit
Shen, Yi
2011-01-01
Recently, many practical algorithms have been proposed to recover the sparse signal from fewer measurements. Orthogonal matching pursuit (OMP) is one of the most effective algorithm. In this paper, we use the restricted isometry property to analysis the algorithm. We show that, under certain conditions based on the restricted isometry property and the signals, OMP will recover the support of the sparse signal when measurements are corrupted by additive noise.
RHIC AND THE PURSUIT OF THE QUARK-GLUON PLASMA.
MITCHELL,J.T.
2001-07-25
There is a fugitive on the loose. Its name is Quark-Gluon Plasma, alias the QGP. The QGP is a known informant with knowledge about the fundamental building blocks of nature that we wish to extract. This briefing will outline the status of the pursuit of the elusive QGP. We will cover what makes the QGP tick, its modus operandi, details on how we plan to hunt the fugitive down, and our level of success thus far.
Wavelet-based multicomponent matching pursuit trace interpolation
Choi, Jihun; Byun, Joongmoo; Seol, Soon Jee; Kim, Young
2016-09-01
Typically, seismic data are sparsely and irregularly sampled due to limitations in the survey environment and these cause problems for key seismic processing steps such as surface-related multiple elimination or wave-equation-based migration. Various interpolation techniques have been developed to alleviate the problems caused by sparse and irregular sampling. Among many interpolation techniques, matching pursuit interpolation is a robust tool to interpolate the regularly sampled data with large receiver separation such as crossline data in marine seismic acquisition when both pressure and particle velocity data are used. Multicomponent matching pursuit methods generally used the sinusoidal basis function, which have shown to be effective for interpolating multicomponent marine seismic data in the crossline direction. In this paper, we report the use of wavelet basis functions which further enhances the performance of matching pursuit methods for de-aliasing than sinusoidal basis functions. We also found that the range of the peak wavenumber of the wavelet is critical to the stability of the interpolation results and the de-aliasing performance and that the range should be determined based on Nyquist criteria. In addition, we reduced the computational cost by adopting the inner product of the wavelet and the input data to find the parameters of the wavelet basis function instead of using L-2 norm minimization. Using synthetic data, we illustrate that for aliased data, wavelet-based matching pursuit interpolation yields more stable results than sinusoidal function-based one when we use not only pressure data only but also both pressure and particle velocity together.
Hierarchical brain networks active in approach and avoidance goal pursuit
Jeffrey Martin Spielberg
2013-06-01
Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.
Smooth ocular pursuit in Chiari type II malformation.
Salman, Michael S; Sharpe, James A; Lillakas, Linda; Steinbach, Martin J; Dennis, Maureen
2007-04-01
Chiari type II malformation (CII) is a congenital anomaly of the cerebellum and brainstem, both important structures for processing smooth ocular pursuit. CII is associated with myelomeningocele and hydrocephalus. We investigated the effects of CII on smooth pursuit (SP) eye movements, and determined the effects of spinal lesion level, number of shunt revisions, nystagmus, and brain dysmorphology on SP. SP was recorded using an infrared eye tracker in 21 participants with CII (11 males, 10 females; age range 8-19y, mean 14y 3mo [SD 3y 2mo]). Thirty-eight healthy children (21 males, 17 females) constituted the comparison group. Participants followed a visual target moving sinusoidally at +/- 10 degrees amplitude, horizontally and vertically at 0.25 or 0.5Hz. SP gains, the ratio of eye to target velocities, were abnormal in the CII group with nystagmus (n= 8). The number of shunt revisions (range 0-10), brain dysmorphology, or spinal lesion level (n= 15 for lower and n= 6 for upper spinal lesion level) did not correlate with SP gains. SP is impaired in children with CII and nystagmus. Abnormal pursuit might be related to the CII dysgenesis or to effects of hydrocephalus. The lack of effect of shunt revisions and abnormal tracking in participants with nystagmus provide evidence that it is related primarily to the cerebellar and brainstem malformation.
Discriminative Elastic-Net Regularized Linear Regression.
Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen
2017-03-01
In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.
[Understanding logistic regression].
El Sanharawi, M; Naudet, F
2013-10-01
Logistic regression is one of the most common multivariate analysis models utilized in epidemiology. It allows the measurement of the association between the occurrence of an event (qualitative dependent variable) and factors susceptible to influence it (explicative variables). The choice of explicative variables that should be included in the logistic regression model is based on prior knowledge of the disease physiopathology and the statistical association between the variable and the event, as measured by the odds ratio. The main steps for the procedure, the conditions of application, and the essential tools for its interpretation are discussed concisely. We also discuss the importance of the choice of variables that must be included and retained in the regression model in order to avoid the omission of important confounding factors. Finally, by way of illustration, we provide an example from the literature, which should help the reader test his or her knowledge.
Langhinrichsen-Rohling, J; Palarea, R E; Cohen, J; Rohling, M L
2000-01-01
This study investigated the prevalence and predictors of unwanted pursuit behaviors among college students. Participants (n = 282) had experienced the termination of a meaningful romantic relationship. Two questionnaires were administered. One assessed unwanted pursuit behaviors that were perpetrated by individuals who had not initiated the relationship breakup (breakup sufferers; n = 120); the other assessed individuals who had initiated the relationship breakup (relationship dissolvers; n = 162). Results indicated that most breakup sufferers had engaged in at least one act of unwanted pursuit (i.e., unwanted phone calls, unwanted in-person conversations) after the breakup. Breakup sufferers were more likely than relationship dissolvers to perceive a positive impact from their unwanted pursuit behavior. Partner-specific attachment experiences and love styles emerged as significant predictors of unwanted pursuit behavior perpetration, according to both victims and perpetrators of unwanted pursuit. However, only victims of unwanted pursuit revealed an association between levels of relationship violence and unwanted pursuit behavior perpetration. Victims also reported that their unwanted pursuit was related to a lack of friendship between themselves and their expartners. In contrast, there was a positive association between feelings of friendship and unwanted pursuit for perpetrators. The implications of these findings and their application to the stalking literature are discussed.
Practical Session: Logistic Regression
Clausel, M.; Grégoire, G.
2014-12-01
An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.
Bache, Stefan Holst
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....
Ritz, Christian; Parmigiani, Giovanni
2009-01-01
R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.
Multiple linear regression analysis
Edwards, T. R.
1980-01-01
Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.
Adaptive metric kernel regression
Goutte, Cyril; Larsen, Jan
2000-01-01
regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...
Software Regression Verification
2013-12-11
of recursive procedures. Acta Informatica , 45(6):403 – 439, 2008. [GS11] Benny Godlin and Ofer Strichman. Regression verifica- tion. Technical Report...functions. Therefore, we need to rede - fine m-term. – Mutual termination. If either function f or function f ′ (or both) is non- deterministic, then their
Seber, George A F
2012-01-01
Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.
Sparse Regression as a Sparse Eigenvalue Problem
Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai
2008-01-01
We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization
Kikuro eFukushima
2011-12-01
Full Text Available Smooth-pursuit eye movements are voluntary responses to small slow-moving objects in the fronto-parallel plane. They evolved in primates, who possess high-acuity foveae, to ensure clear vision about the moving target. The primate frontal cortex contains two smooth-pursuit related areas; the caudal part of the frontal eye fields (FEF and the supplementary eye fields (SEF. Both areas receive vestibular inputs. We review functional differences between the two areas in smooth-pursuit. Most FEF pursuit neurons signal pursuit parameters such as eye velocity and gaze-velocity, and are involved in cancelling the vestibulo-ocular reflex by linear addition of vestibular and smooth-pursuit responses. In contrast, gaze-velocity signals are rarely represented in the SEF. Most FEF pursuit neurons receive neck velocity inputs, while discharge modulation during pursuit and trunk-on-head rotation adds linearly. Linear addition also occurs between neck velocity responses and vestibular responses during head-on-trunk rotation in a task-dependent manner. During cross-axis pursuit-vestibular interactions, vestibular signals effectively initiate predictive pursuit eye movements. Most FEF pursuit neurons discharge during the interaction training after the onset of pursuit eye velocity, making their involvement unlikely in the initial stages of generating predictive pursuit. Comparison of representative signals in the two areas and the results of chemical inactivation during a memory-based smooth-pursuit task indicate they have different roles; the SEF plans smooth-pursuit including working memory of motion-direction, whereas the caudal FEF generates motor commands for pursuit eye movements. Patients with idiopathic Parkinson’s disease were asked to perform this task, since impaired smooth-pursuit and visual working memory deficit during cognitive tasks have been reported in most patients. Preliminary results suggested specific roles of the basal ganglia in memory
Low rank Multivariate regression
Giraud, Christophe
2010-01-01
We consider in this paper the multivariate regression problem, when the target regression matrix $A$ is close to a low rank matrix. Our primary interest in on the practical case where the variance of the noise is unknown. Our main contribution is to propose in this setting a criterion to select among a family of low rank estimators and prove a non-asymptotic oracle inequality for the resulting estimator. We also investigate the easier case where the variance of the noise is known and outline that the penalties appearing in our criterions are minimal (in some sense). These penalties involve the expected value of the Ky-Fan quasi-norm of some random matrices. These quantities can be evaluated easily in practice and upper-bounds can be derived from recent results in random matrix theory.
Subset selection in regression
Miller, Alan
2002-01-01
Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...
Classification and regression trees
Breiman, Leo; Olshen, Richard A; Stone, Charles J
1984-01-01
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Hansen, Henrik; Tarp, Finn
2001-01-01
. There are, however, decreasing returns to aid, and the estimated effectiveness of aid is highly sensitive to the choice of estimator and the set of control variables. When investment and human capital are controlled for, no positive effect of aid is found. Yet, aid continues to impact on growth via...... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes....
Robust Nonstationary Regression
1993-01-01
This paper provides a robust statistical approach to nonstationary time series regression and inference. Fully modified extensions of traditional robust statistical procedures are developed which allow for endogeneities in the nonstationary regressors and serial dependence in the shocks that drive the regressors and the errors that appear in the equation being estimated. The suggested estimators involve semiparametric corrections to accommodate these possibilities and they belong to the same ...
TWO REGRESSION CREDIBILITY MODELS
Constanţa-Nicoleta BODEA
2010-03-01
Full Text Available In this communication we will discuss two regression credibility models from Non – Life Insurance Mathematics that can be solved by means of matrix theory. In the first regression credibility model, starting from a well-known representation formula of the inverse for a special class of matrices a risk premium will be calculated for a contract with risk parameter θ. In the next regression credibility model, we will obtain a credibility solution in the form of a linear combination of the individual estimate (based on the data of a particular state and the collective estimate (based on aggregate USA data. To illustrate the solution with the properties mentioned above, we shall need the well-known representation theorem for a special class of matrices, the properties of the trace for a square matrix, the scalar product of two vectors, the norm with respect to a positive definite matrix given in advance and the complicated mathematical properties of conditional expectations and of conditional covariances.
Visual crowding is anisotropic along the horizontal meridian during smooth pursuit.
Harrison, W J; Remington, R W; Mattingley, J B
2014-01-22
Humans make smooth pursuit eye movements to foveate moving objects of interest. It is known that smooth pursuit alters visual processing, but there is currently no consensus on whether changes in vision are contingent on the direction the eyes are moving. We recently showed that visual crowding can be used as a sensitive measure of changes in visual processing, resulting from involvement of the saccadic eye movement system. The present paper extends these results by examining the effect of smooth pursuit eye movements on the spatial extent of visual crowding-the area over which visual stimuli are integrated. We found systematic changes in crowding that depended on the direction of pursuit and the distance of stimuli from the pursuit target. Relative to when no eye movement was made, the spatial extent of crowding increased for objects located contraversive to the direction of pursuit at an eccentricity of approximately 3°. By contrast, crowding for objects located ipsiversive to the direction of pursuit remained unchanged. There was no change in crowding during smooth pursuit for objects located approximately 7° from the fovea. The increased size of the crowding zone for the contraversive direction may be related to the distance that the fovea lags behind the pursuit target during smooth eye movements. Overall, our results reveal that visual perception is altered dynamically according to the intended destination of oculomotor commands.
Dash, Suryadeep; Thier, Peter
2013-01-01
Smooth-pursuit adaptation (SPA) refers to the fact that pursuit gain in the early, still open-loop response phase of the pursuit eye movement can be adjusted based on experience. For instance, if the target moves initially at a constant velocity for ~100-200 ms and then steps to a higher velocity, subjects learn to up-regulate the pursuit gain associated with the initial target velocity (gain-increase SPA) in order to reduce the retinal error resulting from the velocity step. Correspondingly, a step to a lower target velocity leads to a decrease in gain (gain-decrease SPA). In this study we demonstrate that the increase in peak eye velocity during gain-increase SPA is a consequence of expanding the duration of the eye acceleration profile while the decrease in peak velocity during gain-decrease SPA results from reduced peak eye acceleration but unaltered duration. Furthermore, we show that carrying out stereotypical smooth pursuit eye movements elicited by constant velocity target ramps for several hundred trials (=test of pursuit resilience) leads to a clear drop in initial peak acceleration, a reflection of oculomotor and/or cognitive fatigue. However, this drop in acceleration gets compensated by an increase in the duration of the acceleration profile, thereby keeping initial pursuit gain constant. The compensatory expansion of the acceleration profile in the pursuit resilience experiment is reminiscent of the one leading to gain-increase SPA, suggesting that both processes tap one and the same neuronal mechanism warranting a precise acceleration-duration trade-off. Finally, we show that the ability to adjust acceleration duration during pursuit resilience depends on the integrity of the oculomotor vermis (OMV) as indicated by the complete loss of the duration adjustment following a surgical lesion of the OMV in one rhesus monkey we could study.
Suryadeep eDash
2013-10-01
Full Text Available Smooth-pursuit adaptation (SPA refers to the fact that pursuit gain in the early, still open-loop response phase of the pursuit eye movement can be adjusted based on experience. For instance, if the target moves initially at a constant velocity for approximately 100-200ms and then steps to a higher velocity, subjects learn to up-regulate the pursuit gain associated with the initial target velocity (gain-increase SPA in order to reduce the retinal error resulting from the velocity step. Correspondingly, a step to a lower target velocity leads to a decrease in gain (gain-decrease SPA. In this study we demonstrate that the increase in peak eye velocity during gain-increase SPA is a consequence of expanding the duration of the eye acceleration profile while the decrease in peak velocity during gain-decrease SPA results from reduced peak eye acceleration but unaltered duration. Furthermore, we show that carrying out stereotypical smooth pursuit eye movements elicited by constant velocity target ramps for several hundred trials (= test of pursuit resilience leads to a clear drop in initial peak acceleration, a reflection of oculomotor and/ or cognitive fatigue. However, this drop in acceleration gets compensated by an increase in the duration of the acceleration profile, thereby keeping initial pursuit gain constant. The compensatory expansion of the acceleration profile in the pursuit resilience experiment is reminiscent of the one leading to gain-increase SPA, suggesting that both processes tap one and the same neuronal mechanism warranting a precise acceleration/ duration trade-off. Finally, we show that the ability to adjust acceleration duration during pursuit resilience depends on the integrity of the oculomotor vermis (OMV as indicated by the complete loss of the duration adjustment following a surgical lesion of the OMV in one rhesus monkey we could study.
The relationshipbetween haze and the pursuit of wealth
刘贝赟
2016-01-01
In recent years,China’s economic construction has made unprecedented achievements in development.People’s living standards have been effectively improved,however,along with a wealth of material life,the quality of our environment has significantly decreased,especially in winter in north China,where the haze phenomenon is particularly serious,not only affecting people’s travel and health,but also reducing people’s happiness index.Focusing on the relationship between the haze and the pursuit of wealth,this article will try to explore how to coordinate the relationship between the development of the socio-economy and natural environment.
Effects of priming goal pursuit on implicit sequence learning
Gamble, Katherine R.; Lee, Joanna M.; Howard, James H.; Howard, Darlene V.
2014-01-01
Implicit learning, the type of learning that occurs without intent to learn or awareness of what has been learned, has been thought to be insensitive to the effects of priming, but recent studies suggest this is not the case. One study found that learning in the Serial Reaction Time (SRT) task was improved by nonconscious goal pursuit, primed via a word search task (Eitam et al., 2008). In two studies, we used the goal priming word search task from Eitam et al., but with a different version o...
Qualitative Criterion for Interception in a Pursuit/Evasion Game
Morgan, John A
2009-01-01
A qualitative account is given of a differential pursuit/evasion game. A criterion for the existence of an intercept solution is obtained using future cones that contain all attainable trajectories of target or interceptor originating from an initial position. A sufficient and necessary conditon that an opportunity to intercept always exist is that, after some initial time, the future cone of the target be contained within the future cone of the interceptor. The sufficient condition may be regarded as a kind of Nash equillibrium.
The pursuit of happiness: time, money, and social connection.
Mogilner, Cassie
2010-09-01
Does thinking about time, rather than money, influence how effectively individuals pursue personal happiness? Laboratory and field experiments revealed that implicitly activating the construct of time motivates individuals to spend more time with friends and family and less time working-behaviors that are associated with greater happiness. In contrast, implicitly activating money motivates individuals to work more and socialize less, which (although productive) does not increase happiness. Implications for the relative roles of time versus money in the pursuit of happiness are discussed.
Explaining Factors of Job Pursuit Intention in Indonesian Military Institution
Muhammad Irfan Syaebani
2015-09-01
Full Text Available Reformation brought many changes in public sectors in Indonesia, one of them is Military institution. Reformation required Military to become professional in every organizational aspects, including human resources as a part of resource that need to be manage strategically. Proficient and competent human resource will help organization reach its vision, missons, and strategic goals. One of the strategy to attract competent human resource is to design the recruitment and selection process in talent management corridor, where organization must identify factors which attracting a candidate to join into organization or simply called job pursuit intention. To find out what factors lead to job pursuit intention into military institution in Indonesia, data was collected using qualitative approach from middle-rank military officer. Their past experiences concerning motives/factors which lead them joined into military were explored. From analysis, it reveals that there are 5 factors which make them joined military; employer familiarity, subjective fit, hiring expectation, economic motive, and nationalism/patriotism motive.
Low-bit-rate subband image coding with matching pursuits
Rabiee, Hamid; Safavian, S. R.; Gardos, Thomas R.; Mirani, A. J.
1998-01-01
In this paper, a novel multiresolution algorithm for low bit-rate image compression is presented. High quality low bit-rate image compression is achieved by first decomposing the image into approximation and detail subimages with a shift-orthogonal multiresolution analysis. Then, at the coarsest resolution level, the coefficients of the transformation are encoded by an orthogonal matching pursuit algorithm with a wavelet packet dictionary. Our dictionary consists of convolutional splines of up to order two for the detail and approximation subbands. The intercorrelation between the various resolutions is then exploited by using the same bases from the dictionary to encode the coefficients of the finer resolution bands at the corresponding spatial locations. To further exploit the spatial correlation of the coefficients, the zero trees of wavelets (EZW) algorithm was used to identify the potential zero trees. The coefficients of the presentation are then quantized and arithmetic encoded at each resolution, and packed into a scalable bit stream structure. Our new algorithm is highly bit-rate scalable, and performs better than the segmentation based matching pursuit and EZW encoders at lower bit rates, based on subjective image quality and peak signal-to-noise ratio.
DECISION UTILITY, THE BRAIN, AND PURSUIT OF HEDONIC GOALS
Berridge, Kent C.; Aldridge, J. Wayne
2009-01-01
How do brain representations of the utility of a hedonic goal guide decisions about whether to pursue it? Our focus here will be on brain mechanisms of reward utility operating at particular decision moments in life. Moments such as when you encounter an image, sound, scent or other cue associated in your past with a particular reward; or perhaps just vividly imagine that cue. Such a cue can often trigger a sudden motivational urge to pursue that goal, and sometimes a decision to do so. In drug addicts trying to quit, a cue for the addicted drug might trigger urges that rise to compulsive levels of intensity, despite prior commitments to abstain, leading to the decision to relapse into taking the drug again. Normal or addicted, the urge and decision may well have been lacking immediately before the cue was encountered. The decision to pursue the cued reward might never have happened if the cue had not been encountered. Why can such cues momentarily dominate decision making? The answer involves brain mesolimbic dopamine mechanisms that amplify the incentive salience of reward cues, selectively elevating decision utility to trigger “wanting” for the goal. We describe affective neuroscience studies of brain limbic generators of “wanting” that shed light on how cues trigger pursuit of their goals, both normally and even under intense conditions of irrational goal pursuit. PMID:20198128
MATCHING PURSUITS AMONG SHIFTED CAUCHY KERNELS IN HIGHER-DIMENSIONAL SPACES
钱涛; 王晋勋; 杨燕
2014-01-01
Appealing to the Clifford analysis and matching pursuits, we study the adaptive decompositions of functions of several variables of finite energy under the dictionaries con-sisting of shifted Cauchy kernels. This is a realization of matching pursuits among shifted Cauchy kernels in higher-dimensional spaces. It offers a method to process signals in arbitrary dimensions.
Sparse spikes super-resolution on thin grids II: the continuous basis pursuit
Duval, Vincent; Peyré, Gabriel
2017-09-01
This article analyzes the performance of the continuous basis pursuit (C-BP) method for sparse super-resolution. The C-BP has been recently proposed by Ekanadham, Tranchina and Simoncelli as a refined discretization scheme for the recovery of spikes in inverse problems regularization. One of the most well known discretization scheme, the basis pursuit (BP, also known as \
COMT val(158)met genotype and smooth pursuit eye movements in schizophrenia
Haraldsson, H Magnus; Ettinger, Ulrich; Magnusdottir, Brynja B;
2009-01-01
The association between the catechol-O-methyltransferase (COMT) val(158)met polymorphism (rs4680) and smooth pursuit eye movements (SPEM) was investigated in 110 schizophrenia patients and 96 controls. Patients had lower steady-state pursuit gain and made more frequent saccades than controls...
Modified Regression Correlation Coefficient for Poisson Regression Model
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Karim Hardani*
2012-05-01
Full Text Available A 10-month-old baby presented with developmental delay. He had flaccid paralysis on physical examination.An MRI of the spine revealed malformation of the ninth and tenth thoracic vertebral bodies with complete agenesis of the rest of the spine down that level. The thoracic spinal cord ends at the level of the fifth thoracic vertebra with agenesis of the posterior arches of the eighth, ninth and tenth thoracic vertebral bodies. The roots of the cauda equina appear tightened down and backward and ended into a subdermal fibrous fatty tissue at the level of the ninth and tenth thoracic vertebral bodies (closed meningocele. These findings are consistent with caudal regression syndrome.
Velocity scaling of cue-induced smooth pursuit acceleration obeys constraints of natural motion.
Ladda, Jennifer; Eggert, Thomas; Glasauer, Stefan; Straube, Andreas
2007-09-01
Information about the future trajectory of a visual target is contained not only in the history of target motion but also in static visual cues, e.g., the street provides information about the car's future trajectory. For most natural moving targets, this information imposes strong constraints on the relation between velocity and acceleration which can be exploited by predictive smooth pursuit mechanisms. We questioned how cue-induced predictive changes in pursuit direction depend on target speed and how cue- and target-induced pursuit interact. Subjects pursued a target entering a +/-90 degrees curve and moving on either a homogeneous background or on a low contrast static band indicating the future trajectory. The cue induced a predictive change of pursuit direction, which occurred before curve onset of the target. The predictive velocity component orthogonal to the initial pursuit direction started later and became faster with increasing target velocity. The predictive eye acceleration increased quadratically with target velocity and was independent of the initial target direction. After curve onset, cue- and target-induced pursuit velocity components were not linearly superimposed. The quadratic increase of eye acceleration with target velocity is consistent with the natural velocity scaling implied by the two-thirds power law, which is a characteristic of biological controlled movements. Comparison with linear pursuit models reveals that the ratio between eye acceleration and actual or expected retinal slip cannot be considered a constant gain factor. To obey a natural velocity scaling, this acceleration gain must linearly increase with target or pursuit velocity. We suggest that gain control mechanisms, which affect target-induced changes of pursuit velocity, act similarly on predictive changes of pursuit induced by static visual cues.
Support agnostic Bayesian matching pursuit for block sparse signals
Masood, Mudassir
2013-05-01
A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Stuck in the middle: the psychophysics of goal pursuit.
Bonezzi, Andrea; Brendl, C Miguel; De Angelis, Matteo
2011-05-01
The classic goal-gradient hypothesis posits that motivation to reach a goal increases monotonically with proximity to the desired end state. However, we argue that this is not always the case. In this article, we show that motivation to engage in goal-consistent behavior can be higher when people are either far from or close to the end state and lower when they are about halfway to the end state. We propose a psychophysical explanation for this tendency to get "stuck in the middle." Building on the assumption that motivation is influenced by the perceived marginal value of progress toward the goal, we show that the shape of the goal gradient varies depending on whether an individual monitors progress in terms of distance from the initial state or from the desired end state. Our psychophysical model of goal pursuit predicts a previously undiscovered nonmonotonic gradient, as well as two monotonic gradients.
Deficit of pursuit ocular movements in early Alzheimer's disease
Francesco Cordici; Pietro Lanzafame; Silvia Marino; Alessandro Celona; Lilla Bonanno; Annalisa Baglieri; Alessia Bramanti; Placido Bramanti
2010-01-01
Previous studies have demonstrated that advanced Alzheimer's disease(AD)patients have deficiency of eye movements.However,there have been no reports on eye movement in the early stages of AD.The aim of this study was to evaluate pursuit ocular movements(POM)provided by a vision-based non-intrusive eye tracker in patients with early AD.POM values were significantly lower in AD patients than in normal controls(P < 0.01).In AD patients,POM values were not closely correlated with the Mini-Mental State Examination scores(P = 0.3).There was no significant difference in POM values among patients treated with or without anticholinesterase therapy.We used a vision-based method,for non-intrusive eye tracking,which can be proposed as a possible tool for supporting the diagnosis of early AD.
Detection of neonatal EEG seizure using multichannel matching pursuit.
Khlif, M S; Mesbah, M; Boashash, B; Colditz, P
2008-01-01
It is unusual for a newborn to have the classic "tonic-clonic" seizure experienced by adults and older children. Signs of seizure in newborns are either subtle or may become clinically silent. Therefore, the electroencephalogram (EEG) is becoming the most reliable tool for detecting neonatal seizure. Being non-stationary and multicomponent, EEG signals are suitably analyzed using time-frequency (TF) based methods. In this paper, we present a seizure detection method using a new measure based on the matching pursuit (MP) decomposition of EEG data. Signals are represented in the TF domain where seizure structural characteristics are extracted to form a new coherent TF dictionary to be used in the MP decomposition. A new approach to set data-dependent thresholds, used in the seizure detection process, is proposed. To enhance the performance of the detector, the concept of areas of incidence is utilized to determine the geometrical correlation between EEG recording channels.
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir
2013-11-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean-square error (MMSE) estimate of the sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm
M Sreenivasa Rao
2016-12-01
Full Text Available In this study, we propose compressive sampling matching pursuit (CoSaMP algorithm for sub-Nyquist based electronic warfare (EW receiver system. In compressed sensing (CS theory time-frequency plane localisation and discretisation into a N×N grid in union of subspaces is established. The train of radar signals are sparse in time and frequency can be under sampled with almost no information loss. The CS theory may be applied to EW digital receivers to reduce sampling rate of analog to digital converter; to improve radar parameter resolution and increase input bandwidth. Simulated an efficient approach for radar signal recovery by CoSaMP algorithm by using a set of various sample and different sparsity level with various radar signals. This approach allows a scalable and flexible recovery process. The method has been satisfied with data in a wide frequency range up to 40 GHz. The simulation shows the feasibility of our method.
Recursive Algorithm For Linear Regression
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
Kalman filtering naturally accounts for visually guided and predictive smooth pursuit dynamics.
Orban de Xivry, Jean-Jacques; Coppe, Sébastien; Blohm, Gunnar; Lefèvre, Philippe
2013-10-30
The brain makes use of noisy sensory inputs to produce eye, head, or arm motion. In most instances, the brain combines this sensory information with predictions about future events. Here, we propose that Kalman filtering can account for the dynamics of both visually guided and predictive motor behaviors within one simple unifying mechanism. Our model relies on two Kalman filters: (1) one processing visual information about retinal input; and (2) one maintaining a dynamic internal memory of target motion. The outputs of both Kalman filters are then combined in a statistically optimal manner, i.e., weighted with respect to their reliability. The model was tested on data from several smooth pursuit experiments and reproduced all major characteristics of visually guided and predictive smooth pursuit. This contrasts with the common belief that anticipatory pursuit, pursuit maintenance during target blanking, and zero-lag pursuit of sinusoidally moving targets all result from different control systems. This is the first instance of a model integrating all aspects of pursuit dynamics within one coherent and simple model and without switching between different parallel mechanisms. Our model suggests that the brain circuitry generating a pursuit command might be simpler than previously believed and only implement the functional equivalents of two Kalman filters whose outputs are optimally combined. It provides a general framework of how the brain can combine continuous sensory information with a dynamic internal memory and transform it into motor commands.
Wannez, Sarah; Hoyoux, Thomas; Langohr, Thomas; Bodart, Olivier; Martial, Charlotte; Wertz, Jérôme; Chatelle, Camille; Verly, Jacques G; Laureys, Steven
2017-03-31
Visual pursuit is a key marker of residual consciousness in patients with disorders of consciousness (DOC). Currently, its assessment relies on subjective clinical decisions. In this study, we explore the variability of such clinical assessments, and present an easy-to-use device composed of cameras and video processing algorithms that could help the clinician to improve the detection of visual pursuit in a clinical context. Visual pursuit was assessed by an experienced research neuropsychologist on 31 patients with DOC and on 23 healthy subjects, while the device was used to simultaneously record videos of both one eye and the mirror. These videos were then scored by three researchers: the experienced research neuropsychologist who did the clinical assessment, another experienced research neuropsychologist, and a neurologist. For each video, a consensus was decided between the three persons, and used as the gold standard of the presence or absence of visual pursuit. Almost 10% of the patients were misclassified at the bedside according to their consensus. An automatic classifier analyzed eye and mirror trajectories, and was able to identify patients and healthy subjects with visual pursuit, in total agreement with the consensus on video. In conclusion, our device can be used easily in patients with DOC while respecting the current guidelines of visual pursuit assessment. Our results suggest that our material and our classification method can identify patients with visual pursuit, as well as the three researchers based on video recordings can.
Regression in autistic spectrum disorders.
Stefanatos, Gerry A
2008-12-01
A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.
Combining Alphas via Bounded Regression
Zura Kakushadze
2015-11-01
Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.
Linear regression in astronomy. I
Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh
1990-01-01
Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.
Patterned fabric defect detection via convolutional matching pursuit dual-dictionary
Jing, Junfeng; Fan, Xiaoting; Li, Pengfei
2016-05-01
Automatic patterned fabric defect detection is a promising technique for textile manufacturing due to its low cost and high efficiency. The applicability of most existing algorithms, however, is limited by their intensive computation. To overcome or alleviate the problem, this paper presents a convolutional matching pursuit (CMP) dual-dictionary algorithm for patterned fabric defect detection. A preprocessing with mean sampling is performed to eliminate the influence of background texture of fabric defects. Subsequently, a set of defect-free image blocks are selected as a sample set by sliding window. Dual-dictionary and sparse coefficiencies of the defect-free sample set are obtained via CMP and the K-singular value decomposition (K-SVD) based on a Gabor filter. Then we employ the defect-free and defective fabric image's projections onto the dual-dictionary as features for defect detection. Finally, the test results are determined by comparing the distance between the features to be measured. Experimental results reveal that the proposed algorithm is effective for patterned fabric defect detection and an acceptable average detection rate reaches by 94.2%.
Applying matching pursuit decomposition time-frequency processing to UGS footstep classification
Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.
2013-06-01
The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.
Abnormalities of fixation, saccade and pursuit in posterior cortical atrophy.
Shakespeare, Timothy J; Kaski, Diego; Yong, Keir X X; Paterson, Ross W; Slattery, Catherine F; Ryan, Natalie S; Schott, Jonathan M; Crutch, Sebastian J
2015-07-01
The clinico-neuroradiological syndrome posterior cortical atrophy is the cardinal 'visual dementia' and most common atypical Alzheimer's disease phenotype, offering insights into mechanisms underlying clinical heterogeneity, pathological propagation and basic visual phenomena (e.g. visual crowding). Given the extensive attention paid to patients' (higher order) perceptual function, it is surprising that there have been no systematic analyses of basic oculomotor function in this population. Here 20 patients with posterior cortical atrophy, 17 patients with typical Alzheimer's disease and 22 healthy controls completed tests of fixation, saccade (including fixation/target gap and overlap conditions) and smooth pursuit eye movements using an infrared pupil-tracking system. Participants underwent detailed neuropsychological and neurological examinations, with a proportion also undertaking brain imaging and analysis of molecular pathology. In contrast to informal clinical evaluations of oculomotor dysfunction frequency (previous studies: 38%, current clinical examination: 33%), detailed eyetracking investigations revealed eye movement abnormalities in 80% of patients with posterior cortical atrophy (compared to 17% typical Alzheimer's disease, 5% controls). The greatest differences between posterior cortical atrophy and typical Alzheimer's disease were seen in saccadic performance. Patients with posterior cortical atrophy made significantly shorter saccades especially for distant targets. They also exhibited a significant exacerbation of the normal gap/overlap effect, consistent with 'sticky fixation'. Time to reach saccadic targets was significantly associated with parietal and occipital cortical thickness measures. On fixation stability tasks, patients with typical Alzheimer's disease showed more square wave jerks whose frequency was associated with lower cerebellar grey matter volume, while patients with posterior cortical atrophy showed large saccadic intrusions
Linear Pursuit Differential Game under Phase Constraint on the State of Evader
Askar Rakhmanov
2016-01-01
Full Text Available We consider a linear pursuit differential game of one pursuer and one evader. Controls of the pursuer and evader are subjected to integral and geometric constraints, respectively. In addition, phase constraint is imposed on the state of evader, whereas pursuer moves throughout the space. We say that pursuit is completed, if inclusion y(t1-x(t1∈M is satisfied at some t1>0, where x(t and y(t are states of pursuer and evader, respectively, and M is terminal set. Conditions of completion of pursuit in the game from all initial points of players are obtained. Strategy of the pursuer is constructed so that the phase vector of the pursuer first is brought to a given set, and then pursuit is completed.
In Pursuit of Perspective: Does Linear Perspective Disambiguate Depth from Motion Parallax?
George, Jonathon M.; Johnson, Joshua I.; Nawrot, Mark
2014-01-01
Motion parallax provides a dynamic, unambiguous, monocular visual depth cue. However, the lateral image motion in computer-generated motion parallax displays is depth-sign ambiguous. While mounting evidence indicates that the visual system uses an extra-retinal signal from the pursuit system to disambiguate depth, vertical perspective is a potential confound because it co-varies with the stimulus translation that produces the pursuit signal. Here the role of an extra-retinal pursuit signal and the role of vertical perspective in disambiguating depth from motion parallax were investigated. Through the careful isolation of each cue, the results indicate that observers have excellent depth discrimination with an extra-retinal pursuit cue alone, but have poor discrimination with vertical perspective alone. The conclusion is that vertical perspective does not play a role in the disambiguation of depth in small computer-generated motion parallax displays. PMID:24422245
In pursuit of perspective: does vertical perspective disambiguate depth from motion parallax?
George, Jonathon M; Johnson, Joshua I; Nawrot, Mark
2013-01-01
Motion parallax provides a dynamic, unambiguous, monocular visual depth cue. However, the lateral image motion in computer-generated motion parallax displays is depth-sign ambiguous. While mounting evidence indicates that the visual system uses an extra-retinal signal from the pursuit system to disambiguate depth, vertical perspective is a potential confound because it co-varies with the stimulus translation that produces the pursuit signal. Here the role of an extra-retinal pursuit signal and the role of vertical perspective in disambiguating depth from motion parallax were investigated. Through the careful isolation of each cue, the results indicate that observers have excellent depth discrimination with an extra-retinal pursuit cue alone, but have poor discrimination with vertical perspective alone. The conclusion is that vertical perspective does not play a role in the disambiguation of depth in small computer-generated motion parallax displays.
Isaacs, Rufus
1999-01-01
Definitive work draws on game theory, calculus of variations, and control theory to solve an array of problems: military, pursuit and evasion, athletic contests, many more. Detailed examples, formal calculations. 1965 edition.
Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor
Baofu Fang
2014-01-01
Full Text Available Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots’ individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.
[The comparison of characteristics of smooth pursuit in left-handed and right-handed persons].
Bozhkova, V P; Surovicheva, N S; Nikolaev, D P
2010-01-01
The estimation of the smooth pursuit efficiency in healthy young adults by method based on stroboscopic stimulation is given. The influence of manual function asymmetry on smooth pursuit was tested. Subjects were classified as left-handed or right-handed under a well known handedness questionnaire of Annett supplemented by Luria's tests. It was shown that the strong right-handed persons have a high quality of smooth pursuit of stimuli moving horizontally in rightward and leftward directions with the velocities 20 degrees/s and 25 degrees/s. Left-handed persons track similar stimuli, on the average, worse than the strong right-handed ones. It haven't been observed the influence of manual function asymmetry on the dependence of the smooth pursuit efficiency from the moving stimuli direction (left to right or right to left).
Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.
Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo
2014-01-01
Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.
Time-adaptive quantile regression
Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik
2008-01-01
An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....
Linear regression in astronomy. II
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
- Wave Spectrum of Carbonyl Diazide in Pursuit of Diazirinone
Amberger, Brent K.; Esselman, Brian J.; Woods, R. Claude; McMahon, Robert J.
2013-06-01
Pyrolysis of carbonyl diazide (CO(N_3)_2) has been shown to give diazirinone (CON_2). While diazirione decomposes over the course of a few hours under terrestrial conditions, there is the possibility for it to exist in space. In the pursuit of obtaining a rotational spectrum for diazirinone, we have started with the rotational spectroscopy of its immediate precursor, carbonyl diazide. Carbonyl diazide is highly explosive, and requires careful synthesis. Spectra in the range of 260-360 GHz were collected at room temperature and at -60°C. Ab initio calculations at the CCSD/cc-pVDZ level predict that the conformation where both azide groups are syn to the carbonyl is preferred. A second conformation, where one azide is syn and one is anti, is calculated to lie about 2 kcal/ mol higher in energy. Pure rotational transitions for the ground state and multiple low-lying excited vibrational states of the syn- syn conformation are readily observed and assigned. X. Zeng, H. Beckers, H. Willner and J. F. Stanton, Angew. Chem. Int. Ed. 50 (2011), 1720-1723 A. M. Nolan, B. K. Amberger, B. J. Esselman, V. S. Thimmakondu, J. F. Stanton, R. C. Woods, and R. J. McMahon, Inorg. Chem. 51 (2012), 9846-9851
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.
Han, Lei; Zhang, Yu; Zhang, Tong
2016-08-01
The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.
Effects of priming goal pursuit on implicit sequence learning.
Gamble, Katherine R; Lee, Joanna M; Howard, James H; Howard, Darlene V
2014-11-01
Implicit learning, the type of learning that occurs without intent to learn or awareness of what has been learned, has been thought to be insensitive to the effects of priming, but recent studies suggest this is not the case. One study found that learning in the serial reaction time (SRT) task was improved by nonconscious goal pursuit, primed via a word search task (Eitam et al. in Psychol Sci 19:261-267, 2008). In two studies, we used the goal priming word search task from Eitam et al., but with a different version of the SRT, the alternating serial reaction time task (ASRT). Unlike the SRT, which often results in explicit knowledge and assesses sequence learning at one point in time, the ASRT has been shown to be implicit through sensitive measures of judgment, and it enables sequence learning to be measured continuously. In both studies, we found that implicit learning was superior in the groups that were primed for goal achievement compared to control groups, but the effect was transient. We discuss possible reasons for the observed time course of the positive effects of goal priming, as well as some future areas of investigation to better understand the mechanisms that underlie this effect, which could lead to methods to prolong the positive effects.
Crack growth sparse pursuit for wind turbine blade
Li, Xiang; Yang, Zhibo; Zhang, Han; Du, Zhaohui; Chen, Xuefeng
2015-01-01
One critical challenge to achieving reliable wind turbine blade structural health monitoring (SHM) is mainly caused by composite laminates with an anisotropy nature and a hard-to-access property. The typical pitch-catch PZTs approach generally detects structural damage with both measured and baseline signals. However, the accuracy of imaging or tomography by delay-and-sum approaches based on these signals requires improvement in practice. Via the model of Lamb wave propagation and the establishment of a dictionary that corresponds to scatters, a robust sparse reconstruction approach for structural health monitoring comes into view for its promising performance. This paper proposes a neighbor dictionary that identifies the first crack location through sparse reconstruction and then presents a growth sparse pursuit algorithm that can precisely pursue the extension of the crack. An experiment with the goal of diagnosing a composite wind turbine blade with an artificial crack is performed, and it validates the proposed approach. The results give competitively accurate crack detection with the correct locations and extension length.
Contingencies of self-worth, academic failure, and goal pursuit.
Park, Lora E; Crocker, Jennifer; Kiefer, Amy K
2007-11-01
Two studies examine the effects of failure on explicit and implicit self-esteem, affect, and self-presentation goals as a function of people's trait self-esteem and academic contingency of self-worth. Study 1 shows that participants with low self-esteem (LSE) who receive failure feedback experience lower state self-esteem, less positive affect, and less desire to be perceived as competent the more they base self-worth on academics. In contrast, participants with high self-esteem (HSE) who strongly base self-worth on academics show a slight boost in state self-esteem and desire to be perceived as competent following failure. Study 2 shows that following failure, academically contingent LSE participants downplay the importance of appearing competent to others and associate themselves with failure on an implicit level. Taken together, these findings suggest that academically contingent HSE people show resilience following failure, whereas academically contingent LSE people experience negative outcomes and disengage from the pursuit of competence self-presentation goals.
Newtonized Orthogonal Matching Pursuit: Frequency Estimation Over the Continuum
Mamandipoor, Babak; Ramasamy, Dinesh; Madhow, Upamanyu
2016-10-01
We propose a fast sequential algorithm for the fundamental problem of estimating frequencies and amplitudes of a noisy mixture of sinusoids. The algorithm is a natural generalization of Orthogonal Matching Pursuit (OMP) to the continuum using Newton refinements, and hence is termed Newtonized OMP (NOMP). Each iteration consists of two phases: detection of a new sinusoid, and sequential Newton refinements of the parameters of already detected sinusoids. The refinements play a critical role in two ways: (1) sidestepping the potential basis mismatch from discretizing a continuous parameter space, (2) providing feedback for locally refining parameters estimated in previous iterations. We characterize convergence, and provide a Constant False Alarm Rate (CFAR) based termination criterion. By benchmarking against the Cramer Rao Bound, we show that NOMP achieves near-optimal performance under a variety of conditions. We compare the performance of NOMP with classical algorithms such as MUSIC and more recent Atomic norm Soft Thresholding (AST) and Lasso algorithms, both in terms of frequency estimation accuracy and run time.
Reinforced Intrusion Detection Using Pursuit Reinforcement Competitive Learning
Indah Yulia Prafitaning Tiyas
2014-06-01
Full Text Available Today, information technology is growing rapidly,all information can be obtainedmuch easier. It raises some new problems; one of them is unauthorized access to the system. We need a reliable network security system that is resistant to a variety of attacks against the system. Therefore, Intrusion Detection System (IDS required to overcome the problems of intrusions. Many researches have been done on intrusion detection using classification methods. Classification methodshave high precision, but it takes efforts to determine an appropriate classification model to the classification problem. In this paper, we propose a new reinforced approach to detect intrusion with On-line Clustering using Reinforcement Learning. Reinforcement Learning is a new paradigm in machine learning which involves interaction with the environment.It works with reward and punishment mechanism to achieve solution. We apply the Reinforcement Learning to the intrusion detection problem with considering competitive learning using Pursuit Reinforcement Competitive Learning (PRCL. Based on the experimental result, PRCL can detect intrusions in real time with high accuracy (99.816% for DoS, 95.015% for Probe, 94.731% for R2L and 99.373% for U2R and high speed (44 ms.The proposed approach can help network administrators to detect intrusion, so the computer network security systembecome reliable. Keywords: Intrusion Detection System, On-Line Clustering, Reinforcement Learning, Unsupervised Learning.
Toward Simulating Realistic Pursuit-Evasion Using a Roadmap-Based Approach
Rodriguez, Samuel
2010-01-01
In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. We demonstrate the utility of this approach for a variety of scenarios including pursuit-evasion on terrains, in multi-level buildings, and in crowds. © 2010 Springer-Verlag Berlin Heidelberg.
Spatial contexts can inhibit a mislocalization of visual stimuli during smooth pursuit
Noguchi, Yasuki; Shimojo, Shinsuke; Kakigi, Ryusuke; Hoshiyama, Minoru
2007-01-01
The position of a flash presented during pursuit is mislocalized in the direction of the pursuit. Although this has been explained by a temporal mismatch between the slow visual processing of flash and fast efferent signals on eye positions, here we show that spatial contexts also play an important role in determining the flash position. We put various continuously lit objects (walls) between veridical and to-be-mislocalized positions of flash. Consequently, these walls significantly reduced ...
Polynomial Regression on Riemannian Manifolds
Hinkle, Jacob; Fletcher, P Thomas; Joshi, Sarang
2012-01-01
In this paper we develop the theory of parametric polynomial regression in Riemannian manifolds and Lie groups. We show application of Riemannian polynomial regression to shape analysis in Kendall shape space. Results are presented, showing the power of polynomial regression on the classic rat skull growth data of Bookstein as well as the analysis of the shape changes associated with aging of the corpus callosum from the OASIS Alzheimer's study.
Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models
Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung
2015-01-01
Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…
Quantile regression theory and applications
Davino, Cristina; Vistocco, Domenico
2013-01-01
A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and
Business applications of multiple regression
Richardson, Ronny
2015-01-01
This second edition of Business Applications of Multiple Regression describes the use of the statistical procedure called multiple regression in business situations, including forecasting and understanding the relationships between variables. The book assumes a basic understanding of statistics but reviews correlation analysis and simple regression to prepare the reader to understand and use multiple regression. The techniques described in the book are illustrated using both Microsoft Excel and a professional statistical program. Along the way, several real-world data sets are analyzed in deta
Single-channel and multi-channel orthogonal matching pursuit for seismic trace decomposition
Feng, Xuan; Zhang, Xuebing; Liu, Cai; Lu, Qi
2017-02-01
The conventional matching pursuit (MP) algorithm can decompose a 1D signal into a set of wavelet atoms adaptively. As to reflection seismic data, some applicable algorithms based on the MP decomposition has been developed, such as single-channel matching pursuit (SCMP) and multi-channel matching pursuit (MCMP). However, these algorithms cannot always select the optimal atoms, which results in less meaningful decompositions. To overcome this limitation, we introduce the idea of orthogonal matching pursuit into a multi-channel decomposition scheme, which we refer to as the multi-channel orthogonal matching pursuit (MCOMP). Each iteration of the proposed MCOMP might extract a more reasonable atom among a redundant Morlet wavelet dictionary, like the MCMP decomposition does, and estimate the corresponding amplitude more accurately by solving a least-squares problem. In order to correspond to SCMP, we also simplified the MCOMP decomposition to single-channel orthogonal matching pursuit (SCOMP) for decompositions of an individual seismic trace. We tested the proposed SCOMP algorithm on a synthetic signal and a field seismic trace. Then a field marine dataset example showed relative high resolution of the proposed MCOMP method with applications to the detection of low-frequency anomalies. These application examples all demonstrate more meaningful decomposition results and relative high convergence speed of the proposed algorithms.
Testing discontinuities in nonparametric regression
Dai, Wenlin
2017-01-19
In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100
Logistic Regression: Concept and Application
Cokluk, Omay
2010-01-01
The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…
Fungible weights in logistic regression.
Jones, Jeff A; Waller, Niels G
2016-06-01
In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record
Regression Testing Cost Reduction Suite
Mohamed Alaa El-Din
2014-08-01
Full Text Available The estimated cost of software maintenance exceeds 70 percent of total software costs [1], and large portion of this maintenance expenses is devoted to regression testing. Regression testing is an expensive and frequently executed maintenance activity used to revalidate the modified software. Any reduction in the cost of regression testing would help to reduce the software maintenance cost. Test suites once developed are reused and updated frequently as the software evolves. As a result, some test cases in the test suite may become redundant when the software is modified over time since the requirements covered by them are also covered by other test cases. Due to the resource and time constraints for re-executing large test suites, it is important to develop techniques to minimize available test suites by removing redundant test cases. In general, the test suite minimization problem is NP complete. This paper focuses on proposing an effective approach for reducing the cost of regression testing process. The proposed approach is applied on real-time case study. It was found that the reduction in cost of regression testing for each regression testing cycle is ranging highly improved in the case of programs containing high number of selected statements which in turn maximize the benefits of using it in regression testing of complex software systems. The reduction in the regression test suite size will reduce the effort and time required by the testing teams to execute the regression test suite. Since regression testing is done more frequently in software maintenance phase, the overall software maintenance cost can be reduced considerably by applying the proposed approach.
Rank regression: an alternative regression approach for data with outliers.
Chen, Tian; Tang, Wan; Lu, Ying; Tu, Xin
2014-10-01
Linear regression models are widely used in mental health and related health services research. However, the classic linear regression analysis assumes that the data are normally distributed, an assumption that is not met by the data obtained in many studies. One method of dealing with this problem is to use semi-parametric models, which do not require that the data be normally distributed. But semi-parametric models are quite sensitive to outlying observations, so the generated estimates are unreliable when study data includes outliers. In this situation, some researchers trim the extreme values prior to conducting the analysis, but the ad-hoc rules used for data trimming are based on subjective criteria so different methods of adjustment can yield different results. Rank regression provides a more objective approach to dealing with non-normal data that includes outliers. This paper uses simulated and real data to illustrate this useful regression approach for dealing with outliers and compares it to the results generated using classical regression models and semi-parametric regression models.
ORDINAL REGRESSION FOR INFORMATION RETRIEVAL
无
2008-01-01
This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression problem (i.e. ranking problem) instead of binary classification. It is noted that the task of IR is to rank documents according to the user information needed, so IR can be viewed as ordinal regression problem. Two parameter learning algorithms for ORM are presented. One is a perceptron-based algorithm. The other is the ranking Support Vector Machine (SVM). The effectiveness of the proposed approach has been evaluated on the task of ad hoc retrieval using three English Text REtrieval Conference (TREC) sets and two Chinese TREC sets. Results show that ORM significantly outperforms the state-of-the-art language model approaches and OKAPI system in all test sets; and it is more appropriate to view IR as ordinal regression other than binary classification.
Multiple Regression and Its Discontents
Snell, Joel C.; Marsh, Mitchell
2012-01-01
Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.
Multiple Regression and Its Discontents
Snell, Joel C.; Marsh, Mitchell
2012-01-01
Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.
Regression methods for medical research
Tai, Bee Choo
2013-01-01
Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
Wrong Signs in Regression Coefficients
McGee, Holly
1999-01-01
When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.
From Rasch scores to regression
Christensen, Karl Bang
2006-01-01
Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....
Atamurat Kuchkarov
2016-01-01
Full Text Available We consider pursuit and evasion differential games of a group of m pursuers and one evader on manifolds with Euclidean metric. The motions of all players are simple, and maximal speeds of all players are equal. If the state of a pursuer coincides with that of the evader at some time, we say that pursuit is completed. We establish that each of the differential games (pursuit or evasion is equivalent to a differential game of m groups of countably many pursuers and one group of countably many evaders in Euclidean space. All the players in any of these groups are controlled by one controlled parameter. We find a condition under which pursuit can be completed, and if this condition is not satisfied, then evasion is possible. We construct strategies for the pursuers in pursuit game which ensure completion the game for a finite time and give a formula for this time. In the case of evasion game, we construct a strategy for the evader.
A Pursuit Theory Account for the Perception of Common Motion in Motion Parallax.
Ratzlaff, Michael; Nawrot, Mark
2016-09-01
The visual system uses an extraretinal pursuit eye movement signal to disambiguate the perception of depth from motion parallax. Visual motion in the same direction as the pursuit is perceived nearer in depth while visual motion in the opposite direction as pursuit is perceived farther in depth. This explanation of depth sign applies to either an allocentric frame of reference centered on the fixation point or an egocentric frame of reference centered on the observer. A related problem is that of depth order when two stimuli have a common direction of motion. The first psychophysical study determined whether perception of egocentric depth order is adequately explained by a model employing an allocentric framework, especially when the motion parallax stimuli have common rather than divergent motion. A second study determined whether a reversal in perceived depth order, produced by a reduction in pursuit velocity, is also explained by this model employing this allocentric framework. The results show than an allocentric model can explain both the egocentric perception of depth order with common motion and the perceptual depth order reversal created by a reduction in pursuit velocity. We conclude that an egocentric model is not the only explanation for perceived depth order in these common motion conditions.
Larsson, Linnéa; Nyström, Marcus; Ardö, Håkan; Åström, Kalle; Stridh, Martin
2016-12-01
An increasing number of researchers record binocular eye-tracking signals from participants viewing moving stimuli, but the majority of event-detection algorithms are monocular and do not consider smooth pursuit movements. The purposes of the present study are to develop an algorithm that discriminates between fixations and smooth pursuit movements in binocular eye-tracking signals and to evaluate its performance using an automated video-based strategy. The proposed algorithm uses a clustering approach that takes both spatial and temporal aspects of the binocular eye-tracking signal into account, and is evaluated using a novel video-based evaluation strategy based on automatically detected moving objects in the video stimuli. The binocular algorithm detects 98% of fixations in image stimuli compared to 95% when only one eye is used, while for video stimuli, both the binocular and monocular algorithms detect around 40% of smooth pursuit movements. The present article shows that using binocular information for discrimination of fixations and smooth pursuit movements is advantageous in static stimuli, without impairing the algorithm's ability to detect smooth pursuit movements in video and moving-dot stimuli. With an automated evaluation strategy, time-consuming manual annotations are avoided and a larger amount of data can be used in the evaluation process.
Optimized Projection Matrix for Compressive Sensing
Jianping Xu
2010-01-01
Full Text Available Compressive sensing (CS is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix. Until now, papers on CS always assume the projection matrix to be a random matrix. In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the projection matrix. This method is based on equiangular tight frame (ETF design because an ETF has minimum coherence. It is impossible to solve the problem exactly because of the complexity. Therefore, an alternating minimization type method is used to find a feasible solution. The optimally designed projection matrix can further reduce the necessary number of samples for recovery or improve the recovery accuracy. The proposed method demonstrates better performance than conventional optimization methods, which brings benefits to both basis pursuit and orthogonal matching pursuit.
Analysis of retirement income adequacy using quantile regression: A case study in Malaysia
Alaudin, Ros Idayuwati; Ismail, Noriszura; Isa, Zaidi
2015-09-01
Quantile regression is a statistical analysis that does not restrict attention to the conditional mean and therefore, permitting the approximation of the whole conditional distribution of a response variable. Quantile regression is a robust regression to outliers compared to mean regression models. In this paper, we demonstrate how quantile regression approach can be used to analyze the ratio of projected wealth to needs (wealth-needs ratio) during retirement.
A Matlab program for stepwise regression
Yanhong Qi
2016-03-01
Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.
XRA image segmentation using regression
Jin, Jesse S.
1996-04-01
Segmentation is an important step in image analysis. Thresholding is one of the most important approaches. There are several difficulties in segmentation, such as automatic selecting threshold, dealing with intensity distortion and noise removal. We have developed an adaptive segmentation scheme by applying the Central Limit Theorem in regression. A Gaussian regression is used to separate the distribution of background from foreground in a single peak histogram. The separation will help to automatically determine the threshold. A small 3 by 3 widow is applied and the modal of the local histogram is used to overcome noise. Thresholding is based on local weighting, where regression is used again for parameter estimation. A connectivity test is applied to the final results to remove impulse noise. We have applied the algorithm to x-ray angiogram images to extract brain arteries. The algorithm works well for single peak distribution where there is no valley in the histogram. The regression provides a method to apply knowledge in clustering. Extending regression for multiple-level segmentation needs further investigation.
A Model of the Smooth Pursuit Eye Movement with Prediction and Learning
Davide Zambrano
2010-01-01
Full Text Available Smooth pursuit is one of the five main eye movements in humans, consisting of tracking a steadily moving visual target. Smooth pursuit is a good example of a sensory-motor task that is deeply based on prediction: tracking a visual target is not possible by correcting the error between the eye and the target position or velocity with a feedback loop, but it is only possible by predicting the trajectory of the target. This paper presents a model of smooth pursuit based on prediction and learning. It starts from amodel of the neuro-physiological system proposed by Shibata and Schaal (Shibata et al., Neural Networks, vol. 18, pp. 213-224, 2005. The learning component added here decreases the prediction time in the case of target dynamics already experienced by the system. In the implementation described here, the convergence time is, after the learning phase, 0.8 s.
A New Method of Using Sensor Network for Solving Pursuit-Evasion Problem
Peng Zhuang
2007-02-01
Full Text Available Wireless sensor networks offer the potential to significantly improve the performance of pursuers in pursuit-evasion games. In this paper, we study several sensor network systems, their interaction with the pursuers, and the effect on pursuer performance. We propose a general framework to solve the pursuit-evasion problem and present new centralized as well as distributed methods. Specifically, we address three issues in the design of pursuers based on data provided by the sensor network : a how to identify evader moving patterns, (b how to predict the evader locations using different evader moving models, and c how to choose the most efficient pursuit strategies. We propose efficient algorithms to solve these problems and show that they are effective in reducing the capturing time in our simulations. We also compare the distributed and centralized methods. Experimental results show that the distributed method is efficient and produces solutions close to the centralized method.
Eye movements and hazard perception in police pursuit and emergency response driving.
Crundall, David; Chapman, Peter; Phelps, Nicola; Underwood, Geoffrey
2003-09-01
How do police cope with the visual demands placed on them during pursuit driving? This study compared the hazard ratings, eye movements, and physiological responses of police drivers with novice and with age-matched control drivers while viewing video clips of driving taken from police vehicles. The clips included pursuits, emergency responses, and control drives. Although police drivers did not report more hazards than the other participants reported, they had an increased frequency of electrodermal responses while viewing dangerous clips and a greater visual sampling rate and spread of search. However, despite an overall police advantage in oculomotor and physiological measures, all drivers had a reduced spread of search in nighttime pursuits because of the focusing of overt attention.
Biplots in Reduced-Rank Regression
Braak, ter C.J.F.; Looman, C.W.N.
1994-01-01
Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal c
Interpretation of Standardized Regression Coefficients in Multiple Regression.
Thayer, Jerome D.
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for…
Saccadic and smooth-pursuit eye movements during reading of drifting texts.
Valsecchi, Matteo; Gegenfurtner, Karl R; Schütz, Alexander C
2013-08-16
Reading is a complex visuomotor behavior characterized by an alternation of fixations and saccadic eye movements. Despite the widespread use of drifting texts in various settings, very little is known about eye movements under these conditions. Here we investigated oculomotor behavior during reading of texts which were drifting horizontally or vertically at different speeds. Consistent with previous reports, drifting texts were read by an alternation of smooth-pursuit and saccadic eye movements. Detailed analysis revealed several interactions between smooth pursuit and saccades. On one side, the gain of smooth pursuit was increased after the execution of a saccade. On the other side, the peak velocity of saccades was reduced for the horizontally drifting text, in which saccades and pursuit were executed in opposite directions. In addition, we show that well-known findings from the reading of static texts extend to drifting text, such as the preferred viewing location, the inverted optimal viewing position, and the correlation between saccade amplitude and subsequent pursuit/fixation duration. In general, individual eye-movement parameters such as saccade amplitude and fixation/pursuit durations were correlated across self-paced reading of static text and time-constrained reading of static and drifting texts. These results show that findings from basic oculomotor research also apply to the reading of drifting texts. Similarly, basic reading principles apply to the reading of static and drifting texts in a similar way. This exemplifies the reading of drifting text as a visuomotor behavior which is influenced by low-level eye-movement control as well as by cognitive and linguistic processing.
Inferential Models for Linear Regression
Zuoyi Zhang
2011-09-01
Full Text Available Linear regression is arguably one of the most widely used statistical methods in applications. However, important problems, especially variable selection, remain a challenge for classical modes of inference. This paper develops a recently proposed framework of inferential models (IMs in the linear regression context. In general, an IM is able to produce meaningful probabilistic summaries of the statistical evidence for and against assertions about the unknown parameter of interest and, moreover, these summaries are shown to be properly calibrated in a frequentist sense. Here we demonstrate, using simple examples, that the IM framework is promising for linear regression analysis --- including model checking, variable selection, and prediction --- and for uncertain inference in general.
[Is regression of atherosclerosis possible?].
Thomas, D; Richard, J L; Emmerich, J; Bruckert, E; Delahaye, F
1992-10-01
Experimental studies have shown the regression of atherosclerosis in animals given a cholesterol-rich diet and then given a normal diet or hypolipidemic therapy. Despite favourable results of clinical trials of primary prevention modifying the lipid profile, the concept of atherosclerosis regression in man remains very controversial. The methodological approach is difficult: this is based on angiographic data and requires strict standardisation of angiographic views and reliable quantitative techniques of analysis which are available with image processing. Several methodologically acceptable clinical coronary studies have shown not only stabilisation but also regression of atherosclerotic lesions with reductions of about 25% in total cholesterol levels and of about 40% in LDL cholesterol levels. These reductions were obtained either by drugs as in CLAS (Cholesterol Lowering Atherosclerosis Study), FATS (Familial Atherosclerosis Treatment Study) and SCOR (Specialized Center of Research Intervention Trial), by profound modifications in dietary habits as in the Lifestyle Heart Trial, or by surgery (ileo-caecal bypass) as in POSCH (Program On the Surgical Control of the Hyperlipidemias). On the other hand, trials with non-lipid lowering drugs such as the calcium antagonists (INTACT, MHIS) have not shown significant regression of existing atherosclerotic lesions but only a decrease on the number of new lesions. The clinical benefits of these regression studies are difficult to demonstrate given the limited period of observation, relatively small population numbers and the fact that in some cases the subjects were asymptomatic. The decrease in the number of cardiovascular events therefore seems relatively modest and concerns essentially subjects who were symptomatic initially. The clinical repercussion of studies of prevention involving a single lipid factor is probably partially due to the reduction in progression and anatomical regression of the atherosclerotic plaque
Nonparametric regression with filtered data
Linton, Oliver; Nielsen, Jens Perch; Van Keilegom, Ingrid; 10.3150/10-BEJ260
2011-01-01
We present a general principle for estimating a regression function nonparametrically, allowing for a wide variety of data filtering, for example, repeated left truncation and right censoring. Both the mean and the median regression cases are considered. The method works by first estimating the conditional hazard function or conditional survivor function and then integrating. We also investigate improved methods that take account of model structure such as independent errors and show that such methods can improve performance when the model structure is true. We establish the pointwise asymptotic normality of our estimators.
Logistic regression for circular data
Al-Daffaie, Kadhem; Khan, Shahjahan
2017-05-01
This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.
Quasi-least squares regression
Shults, Justine
2014-01-01
Drawing on the authors' substantial expertise in modeling longitudinal and clustered data, Quasi-Least Squares Regression provides a thorough treatment of quasi-least squares (QLS) regression-a computational approach for the estimation of correlation parameters within the framework of generalized estimating equations (GEEs). The authors present a detailed evaluation of QLS methodology, demonstrating the advantages of QLS in comparison with alternative methods. They describe how QLS can be used to extend the application of the traditional GEE approach to the analysis of unequally spaced longitu
Reduction of snapshots for MIMO radar detection by block/group orthogonal matching pursuit
Ali, Hussain El Hosiny
2014-10-01
Multiple-input multiple-output (MIMO) radar works on the principle of transmission of independent waveforms at each element of its antenna array and is widely used for surveillance purposes. In this work, we investigate MIMO radar target localization problem with compressive sensing. Specifically, we try to solve the problem of estimation of target location in MIMO radar by group and block sparsity algorithms. It will lead us to a reduced number of snapshots required and also we can achieve better radar resolution. We will use group orthogonal matching pursuit (GOMP) and block orthogonal matching pursuit (BOMP) for our problem. © 2014 IEEE.
Zhao Ruizhen; Ren Xiaoxin; Han Xuelian; Hu Shaohai
2012-01-01
Sparsity Adaptive Matching Pursuit (SAMP) algorithm is a widely used reconstruction algorithm for compressive sensing in the case that the sparsity is unknown.In order to match the sparsity more accurately,we presented an improved SAMP algorithm based on Regularized Backtracking (SAMP-RB).By adapting a regularized backtracking step to SAMP algorithm in each iteration stage,the proposed algorithm can flexibly remove the inappropriate atoms.The experimental results show that SAMP-RB reconstruction algorithm greatly improves SAMP algorithm both in reconstruction quality and computational time.It has better reconstruction efficiency than most of the available matching pursuit algorithms.
The relationship between disordered pursuit and vestibulo-ocular reflex suppression
Chambers, Br; Gresty, MA
1983-01-01
The performance of the smooth pursuit reflex and the ability to suppress the vestibulo-ocular reflex were assessed in 10 normal subjects and in patients with a variety of diseases of the central nervous system. Pursuit was measured as the maximum velocity of slow phase eye movement in response to a laser target moving sinusoidally at various frequencies up to 1 Hz and with amplitudes stepped up to 35° peak. Suppression of the vestibulo-ocular reflex was assessed with subjects seated in a Bara...
Roczniewska, Marta; Retowski, Sylwiusz
2014-01-01
Person-organization (P-O) fit is a predictor of job satisfaction, and a misfit is a potential stressor. We aimed to examine the consequences of fit between a person and an organization in terms of goal pursuit strategies. We tested whether job satisfaction mediates the relationship between regulatory fit and mental health. Research was conducted in a group of 169 employees. They were asked to fill in questionnaires assessing their chronic work regulatory focus, organiza tional regulatory focus and job satisfaction. To measure mental well-being we administered the General Health Questionnaire (GHQ-28). We conducted mediation analysis in regression. The results of the mediation analysis confirmed the me- diating role of job satisfaction in the relation between regulatory focus misfit and physical and mental symptoms of distress. The results of this study point to the fact that P-O fit can relate to goal pursuit strategies. It influences not only job satisfaction, but also employees' health.The conclusions can be applied in the human resources management practices, e.g., it may serve as a useful argument to motivate employers to shape goals and strategies individually by managers, according to employees preferences. The results should be interpreted with caution because of non-random sampling.
Marta Roczniewska
2014-10-01
Full Text Available Background: Person-organization (P–O fit is a predictor of job satisfaction, and a misfit is a potential stressor. We aimed to examine the consequences of fit between a person and an organization in terms of goal-pursuit strategies. We tested whether job satisfaction mediates the relationship between regulatory fit and mental health. Material and Methods: Research was conducted in a group of 169 employees. They were asked to fill in questionnaires assessing their chronic work regulatory focus, organizational regulatory focus and job satisfaction. To measure mental well-being we administered the General Health Questionnaire (GHQ-28. We conducted mediation analysis in regression. Results: The results of the mediation analysis confirmed the mediating role of job satisfaction in the relation between regulatory focus misfit and physical and mental symptoms of distress. Conclusions: The results of this study point to the fact that P–O fit can relate to goal pursuit strategies. It influences not only job satisfaction, but also employees’ health. The conclusions can be applied in the human resources management practices, e.g., it may serve as a useful argument to motivate employers to shape goals and strategies individually by managers, according to employees’ preferences. The results should be interpreted with caution because of non-random sampling. Med Pr 2014;65(5:621–631
Multi-Objective Genetic Programming Projection Pursuit for Exploratory Data Modeling
Icke, Ilknur
2010-01-01
For classification problems, feature extraction is a crucial process which aims to find a suitable data representation that increases the performance of the machine learning algorithm. According to the curse of dimensionality theorem, the number of samples needed for a classification task increases exponentially as the number of dimensions (variables, features) increases. On the other hand, it is costly to collect, store and process data. Moreover, irrelevant and redundant features might hinder classifier performance. In exploratory analysis settings, high dimensionality prevents the users from exploring the data visually. Feature extraction is a two-step process: feature construction and feature selection. Feature construction creates new features based on the original features and feature selection is the process of selecting the best features as in filter, wrapper and embedded methods. In this work, we focus on feature construction methods that aim to decrease data dimensionality for visualization tasks. V...
Hyvonen, Katriina; Feldt, Taru; Tolvanen, Asko; Kinnunen, Ulla
2010-01-01
The relation of the core components of the Effort-Reward Imbalance model (ERI; Siegrist, 1996) to goal pursuit was investigated. Goal pursuit was studied through categories of goal contents--competency, progression, well-being, job change, job security, organization, finance, or no work goal--based on the personal work goals of managers (Hyvonen,…
Kongsted, Alice; Jørgensen, L V; Bendix, T
2007-01-01
To evaluate whether smooth pursuit eye movements differed between patients with long-lasting whiplash-associated disorders and controls when using a purely computerized method for the eye movement analysis.......To evaluate whether smooth pursuit eye movements differed between patients with long-lasting whiplash-associated disorders and controls when using a purely computerized method for the eye movement analysis....
C Pallus, Adam; G Freedman, Edward
2016-08-01
Gaze pursuit is the coordinated movement of the eyes and head that allows humans and other foveate animals to track moving objects. The control of smooth pursuit eye movements when the head is restrained is relatively well understood, but how the eyes coordinate with concurrent head movements when the head is free remains unresolved. In this study, we describe behavioral tasks that dissociate head and gaze velocity during head-free pursuit in monkeys. Existing models of gaze pursuit propose that both eye and head movements are driven only by the perceived velocity of the visual target and are therefore unable to account for these data. We show that in addition to target velocity, the positions of the eyes in the orbits and the retinal position of the target are important factors for predicting head movement during pursuit. When the eyes are already near their limits, further pursuit in that direction will be accompanied by more head movement than when the eyes are centered in the orbits, even when target velocity is the same. The step-ramp paradigm, often used in pursuit tasks, produces larger or smaller head movements, depending on the direction of the position step, while gaze pursuit velocity is insensitive to this manipulation. Using these tasks, we can reliably evoke head movements with peak velocities much faster than the target's velocity. Under these circumstances, the compensatory eye movements, which are often called counterproductive since they rotate the eyes in the opposite direction, are essential to maintaining accurate gaze velocity.
Regression of lumbar disk herniation
G. Yu Evzikov
2015-01-01
Full Text Available Compression of the spinal nerve root, giving rise to pain and sensory and motor disorders in the area of its innervation is the most vivid manifestation of herniated intervertebral disk. Different treatment modalities, including neurosurgery, for evolving these conditions are discussed. There has been recent evidence that spontaneous regression of disk herniation can regress. The paper describes a female patient with large lateralized disc extrusion that has caused compression of the nerve root S1, leading to obvious myotonic and radicular syndrome. Magnetic resonance imaging has shown that the clinical manifestations of discogenic radiculopathy, as well myotonic syndrome and morphological changes completely regressed 8 months later. The likely mechanism is inflammation-induced resorption of a large herniated disk fragment, which agrees with the data available in the literature. A decision to perform neurosurgery for which the patient had indications was made during her first consultation. After regression of discogenic radiculopathy, there was only moderate pain caused by musculoskeletal diseases (facet syndrome, piriformis syndrome that were successfully eliminated by minimally invasive techniques.
Heteroscedasticity checks for regression models
无
2001-01-01
For checking on heteroscedasticity in regression models, a unified approach is proposed to constructing test statistics in parametric and nonparametric regression models. For nonparametric regression, the test is not affected sensitively by the choice of smoothing parameters which are involved in estimation of the nonparametric regression function. The limiting null distribution of the test statistic remains the same in a wide range of the smoothing parameters. When the covariate is one-dimensional, the tests are, under some conditions, asymptotically distribution-free. In the high-dimensional cases, the validity of bootstrap approximations is investigated. It is shown that a variant of the wild bootstrap is consistent while the classical bootstrap is not in the general case, but is applicable if some extra assumption on conditional variance of the squared error is imposed. A simulation study is performed to provide evidence of how the tests work and compare with tests that have appeared in the literature. The approach may readily be extended to handle partial linear, and linear autoregressive models.
Cactus: An Introduction to Regression
Hyde, Hartley
2008-01-01
When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…
Growth Regression and Economic Theory
Elbers, Chris; Gunning, Jan Willem
2002-01-01
In this note we show that the standard, loglinear growth regression specificationis consistent with one and only one model in the class of stochastic Ramsey models. Thismodel is highly restrictive: it requires a Cobb-Douglas technology and a 100% depreciationrate and it implies that risk does not af
Correlation Weights in Multiple Regression
Waller, Niels G.; Jones, Jeff A.
2010-01-01
A general theory on the use of correlation weights in linear prediction has yet to be proposed. In this paper we take initial steps in developing such a theory by describing the conditions under which correlation weights perform well in population regression models. Using OLS weights as a comparison, we define cases in which the two weighting…
Ridge Regression for Interactive Models.
Tate, Richard L.
1988-01-01
An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are favorable to…
Logistic regression: a brief primer.
Stoltzfus, Jill C
2011-10-01
Regression techniques are versatile in their application to medical research because they can measure associations, predict outcomes, and control for confounding variable effects. As one such technique, logistic regression is an efficient and powerful way to analyze the effect of a group of independent variables on a binary outcome by quantifying each independent variable's unique contribution. Using components of linear regression reflected in the logit scale, logistic regression iteratively identifies the strongest linear combination of variables with the greatest probability of detecting the observed outcome. Important considerations when conducting logistic regression include selecting independent variables, ensuring that relevant assumptions are met, and choosing an appropriate model building strategy. For independent variable selection, one should be guided by such factors as accepted theory, previous empirical investigations, clinical considerations, and univariate statistical analyses, with acknowledgement of potential confounding variables that should be accounted for. Basic assumptions that must be met for logistic regression include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers. Additionally, there should be an adequate number of events per independent variable to avoid an overfit model, with commonly recommended minimum "rules of thumb" ranging from 10 to 20 events per covariate. Regarding model building strategies, the three general types are direct/standard, sequential/hierarchical, and stepwise/statistical, with each having a different emphasis and purpose. Before reaching definitive conclusions from the results of any of these methods, one should formally quantify the model's internal validity (i.e., replicability within the same data set) and external validity (i.e., generalizability beyond the current sample). The resulting logistic regression model
Environmentalism and Science: Politics and the Pursuit of Knowledge.
Rycroft, Robert W.
1991-01-01
Examination of the relationship between environmentalists and scientists concludes that environmentalism has had little impact on science. Topics discussed include the degree to which scientific research has become more applied; efforts to integrate and coordinate research projects; the synthesis of scientific information for policy purposes; and…
Regression Verification Using Impact Summaries
Backes, John; Person, Suzette J.; Rungta, Neha; Thachuk, Oksana
2013-01-01
Regression verification techniques are used to prove equivalence of syntactically similar programs. Checking equivalence of large programs, however, can be computationally expensive. Existing regression verification techniques rely on abstraction and decomposition techniques to reduce the computational effort of checking equivalence of the entire program. These techniques are sound but not complete. In this work, we propose a novel approach to improve scalability of regression verification by classifying the program behaviors generated during symbolic execution as either impacted or unimpacted. Our technique uses a combination of static analysis and symbolic execution to generate summaries of impacted program behaviors. The impact summaries are then checked for equivalence using an o-the-shelf decision procedure. We prove that our approach is both sound and complete for sequential programs, with respect to the depth bound of symbolic execution. Our evaluation on a set of sequential C artifacts shows that reducing the size of the summaries can help reduce the cost of software equivalence checking. Various reduction, abstraction, and compositional techniques have been developed to help scale software verification techniques to industrial-sized systems. Although such techniques have greatly increased the size and complexity of systems that can be checked, analysis of large software systems remains costly. Regression analysis techniques, e.g., regression testing [16], regression model checking [22], and regression verification [19], restrict the scope of the analysis by leveraging the differences between program versions. These techniques are based on the idea that if code is checked early in development, then subsequent versions can be checked against a prior (checked) version, leveraging the results of the previous analysis to reduce analysis cost of the current version. Regression verification addresses the problem of proving equivalence of closely related program
Curry, Marnie W.
2012-01-01
In the ideal, reciprocity in qualitative inquiry occurs when there is give-and-take between researchers and the researched; however, the demands of the academy and resource constraints often make the pursuit of reciprocity difficult. Drawing on two video-based, qualitative studies in which researchers utilized video records as resources to enhance…
Modeling depth from motion parallax with the motion/pursuit ratio
Mark eNawrot
2014-10-01
Full Text Available The perception of unambiguous scaled depth from motion parallax relies on both retinal image motion and an extra-retinal pursuit eye movement signal. The motion/pursuit ratio represents a dynamic geometric model linking these two proximal cues to the ratio of depth to viewing distance. An important step in understanding the visual mechanisms serving the perception of depth from motion parallax is to determine the relationship between these stimulus parameters and empirically determined perceived depth magnitude. Observers compared perceived depth magnitude of dynamic motion parallax stimuli to static binocular disparity comparison stimuli at three different viewing distances, in both head-moving and head-stationary conditions. A stereo-viewing system provided ocular separation for stereo stimuli and monocular viewing of parallax stimuli. For each motion parallax stimulus, a point of subjective equality was estimated for the amount of binocular disparity that generates the equivalent magnitude of perceived depth from motion parallax. Similar to previous results, perceived depth from motion parallax had significant foreshortening. Head-moving conditions produced even greater foreshortening due to the differences in the compensatory eye movement signal. An empirical version of motion/pursuit law, termed the empirical motion/pursuit ratio, which models perceived depth magnitude from these stimulus parameters, is proposed.
Modeling depth from motion parallax with the motion/pursuit ratio.
Nawrot, Mark; Ratzlaff, Michael; Leonard, Zachary; Stroyan, Keith
2014-01-01
The perception of unambiguous scaled depth from motion parallax relies on both retinal image motion and an extra-retinal pursuit eye movement signal. The motion/pursuit ratio represents a dynamic geometric model linking these two proximal cues to the ratio of depth to viewing distance. An important step in understanding the visual mechanisms serving the perception of depth from motion parallax is to determine the relationship between these stimulus parameters and empirically determined perceived depth magnitude. Observers compared perceived depth magnitude of dynamic motion parallax stimuli to static binocular disparity comparison stimuli at three different viewing distances, in both head-moving and head-stationary conditions. A stereo-viewing system provided ocular separation for stereo stimuli and monocular viewing of parallax stimuli. For each motion parallax stimulus, a point of subjective equality (PSE) was estimated for the amount of binocular disparity that generates the equivalent magnitude of perceived depth from motion parallax. Similar to previous results, perceived depth from motion parallax had significant foreshortening. Head-moving conditions produced even greater foreshortening due to the differences in the compensatory eye movement signal. An empirical version of the motion/pursuit law, termed the empirical motion/pursuit ratio, which models perceived depth magnitude from these stimulus parameters, is proposed.
Information fusion control with time delay for smooth pursuit eye movement.
Zhang, Menghua; Ma, Xin; Qin, Bin; Wang, Guangmao; Guo, Yanan; Xu, Zhigang; Wang, Yafang; Li, Yibin
2016-05-01
Smooth pursuit eye movement depends on prediction and learning, and is subject to time delays in the visual pathways. In this paper, an information fusion control method with time delay is presented, implementing smooth pursuit eye movement with prediction and learning as well as solving the problem of time delays in the visual pathways. By fusing the soft constraint information of the target trajectory of eyes and the ideal control strategy, and the hard constraint information of the eye system state equation and the output equation, optimal estimations of the co-state sequence and the control variable are obtained. The proposed control method can track not only constant velocity, sinusoidal target motion, but also arbitrary moving targets. Moreover, the absolute value of the retinal slip reaches steady state after 0.1 sec. Information fusion control method elegantly describes in a function manner how the brain may deal with arbitrary target velocities, how it implements the smooth pursuit eye movement with prediction, learning, and time delays. These two principles allowed us to accurately describe visually guided, predictive and learning smooth pursuit dynamics observed in a wide variety of tasks within a single theoretical framework. The tracking control performance of the proposed information fusion control with time delays is verified by numerical simulation results.
Physical Activities and Sedentary Pursuits in African American and Caucasian Girls
Dowda, Marsha; Pate, Russell R.; Felton, Gwen M.; Saunders, Ruth; Ward, Dianne S.; Dishman, Rod K.; Trost, Stewart G.
2004-01-01
The purposes of this study were to describe and compare the specific physical activity choices and sedentary pursuits of African American and Caucasian American girls. Participants were 1,124 African American and 1,068 Caucasian American eighth-grade students from 31 middle schools. The 3-Day Physical Activity Recall (3DPAR) was used to measure…
The Role of an Epistemology of Inclusivity on the Pursuit of Social Justice: A Case Study
Scanlan, Martin
2012-01-01
Social justice education emphasizes how schools can better serve traditionally marginalized students. This case study examines the pursuit of social justice education in an unlikely setting: a Catholic elementary school that both espouses inclusion of all children and effectively includes children with a wide range of disabilities. The article…
38 CFR 21.314 - Pursuit of training under special conditions.
2010-07-01
... is required to pursue a rehabilitation program at a rate which meets the requirement for full- or... rehabilitation program at a lesser rate, if such pursuit is a part of the veteran's plan. Subsistence allowance... AFFAIRS (CONTINUED) VOCATIONAL REHABILITATION AND EDUCATION Vocational Rehabilitation and Employment...
Raghavan, Ramanujan T; Joshua, Mati
2017-07-19
We investigated the composition of preparatory activity of frontal eye field (FEF) neurons in monkeys performing a pursuit target selection task. In response to the orthogonal motion of a large and a small reward target, monkeys initiated pursuit biased towards the direction of large reward target motion. FEF neurons exhibited robust preparatory activity preceding movement initiation in this task. Preparatory activity consisted of two components, ramping activity that was constant across target selection conditions and a flat offset in firing rates that signaled the target selection condition. Ramping activity accounted for 50% of the variance in the preparatory activity and was linked most strongly, on a trial-by-trial basis, to pursuit eye movement latency rather than to its direction or gain. The offset in firing rates that discriminated target selection conditions accounted for 25% of the variance in the preparatory activity, and was commensurate with a winner-take-all representation signaling the direction of large reward target motion rather than a representation that matched the parameters of the upcoming movement. These offer new insights into the role the frontal eye fields play in target selection and pursuit control. They show that preparatory activity in the FEF signals more strongly when to move rather than where or how to move, and suggest that structures outside the FEF augment its contributions to the target selection process. Copyright © 2017, Journal of Neurophysiology.
Coping with spinal cord injury: Tenacious goal pursuit and flexible goal adjustment.
van Lankveld, Wim; van Diemen, Tijn; van Nes, Ilse J. W.
2011-01-01
Objective: To investigate the correlation of higher-order coping strategies of tenacious goal pursuit and flexible goal adjustment with adjustment after rehabilitation in spinal cordinjury. Design: Cross-sectional correlational study.Subjects/patients: All 397 eligible patients entered for spinal
Kong, Xiaoqing; Chakraverty, Devasmita; Jeffe, Donna B.; Andriole, Dorothy A.; Wathington, Heather D.; Tai, Robert H.
2013-01-01
This exploratory qualitative study investigated how doctoral students reported their personal and professional interaction experiences that they believed might facilitate or impede their academic pursuits in biomedical research. We collected 19 in-depth interviews with doctoral students in biomedical research from eight universities, and we based…
When goal pursuit fails: The functions of counterfactual thought in intention formation
Epstude, K.; Roese, N.J.
2011-01-01
Counterfactual thoughts predominantly occur in response to failed goal pursuit. The primary function of self-related counterfactuals seems to be correction of specific behaviors and preparation for future successful goal attainment. In the present article we describe a model that outlines this view
The Role of Intrinsic Motivation in the Academic Pursuits of Nontraditional Students
Shillingford, Shani; Karlin, Nancy J.
2013-01-01
This article examines the role of intrinsic motivation in the academic pursuits of nontraditional students. The Academic Motivational Scale (AMS) was administered to 35 undergraduate students, 6 males and 29 females, aged 25 to 49 to explore their motivational orientations in choosing to attend college. The results of the study show that…
On Discrete-Time Pursuit-Evasion Games with Sensing Limitations
2008-01-01
different number of pursuers. Index Terms Pursuit-evasion games, sensing limitations, cooperative control. Paper type: Technical Report Number CCDC -08-0313...Cover Note: Shaunak D. Bopardikar, Francesco Bullo and João P. Hespanha are with the Center for Control, Dynamical systems and Computation ( CCDC
Dynamics of the echolocation beam during prey pursuit in aerial hawking bats.
Jakobsen, Lasse; Olsen, Mads Nedergaard; Surlykke, Annemarie
2015-06-30
In the evolutionary arms race between prey and predator, measures and countermeasures continuously evolve to increase survival on both sides. Bats and moths are prime examples. When exposed to intense ultrasound, eared moths perform dramatic escape behaviors. Vespertilionid and rhinolophid bats broaden their echolocation beam in the final stage of pursuit, presumably as a countermeasure to keep evading moths within their "acoustic field of view." In this study, we investigated if dynamic beam broadening is a general property of echolocation when catching moving prey. We recorded three species of emballonurid bats, Saccopteryx bilineata, Saccopteryx leptura, and Rhynchonycteris naso, catching airborne insects in the field. The study shows that S. bilineata and S. leptura maintain a constant beam shape during the entire prey pursuit, whereas R. naso broadens the beam by lowering the peak call frequency from 100 kHz during search and approach to 67 kHz in the buzz. Surprisingly, both Saccopteryx bats emit calls with very high energy throughout the pursuit, up to 60 times more than R. naso and Myotis daubentonii (a similar sized vespertilionid), providing them with as much, or more, peripheral "vision" than the vespertilionids, but ensonifying objects far ahead suggesting more clutter. Thus, beam broadening is not a fundamental property of the echolocation system. However, based on the results, we hypothesize that increased peripheral detection is crucial to all aerial hawking bats in the final stages of prey pursuit and speculate that beam broadening is a feature characterizing more advanced echolocation.
Bijleveld, E.H.; Custers, R.; Aarts, H.A.G.
2012-01-01
When in pursuit of rewards, humans weigh the value of potential rewards against the amount of effort that is required to attain them. Although previous research has generally conceptualized this process as a deliberate calculation, recent work suggests that rudimentary mechanisms operating without c
Bijleveld, Erik; Custers, Ruud; Aarts, Henk
2012-01-01
When in pursuit of rewards, humans weigh the value of potential rewards against the amount of effort that is required to attain them. Although previous research has generally conceptualized this process as a deliberate calculation, recent work suggests that rudimentary mechanisms--operating without conscious intervention--play an important role as…
A* Orthogonal Matching Pursuit: Best-First Search for Compressed Sensing Signal Recovery
Karahanoglu, Nazim Burak
2010-01-01
Compressed sensing is a recently developing area which is interested in reconstruction of sparse signals acquired in reduced dimensions. Acquiring the data with a small number of samples makes the reconstruction problem under-determined. The required solution is the one with minimum $l_0$ norm due to sparsity, however it is not practical to solve the $l_0$ minimization problem. Some methods, such as Basis Pursuit (BP) propose casting the problem as an $l_1$ minimization. Greedy pursuit algorithms, such as Orthogonal Matching Pursuit (OMP) and Subspace Pursuit (SP), perform a greedy search among the vectors in the basis with the goal of stagewise constrained minimization of the residual error. This manuscript proposes a new semi-greedy algorithm which employs a best-first search technique, the A* search. This approach searches for the solution on several paths of a search tree, where the paths are evaluated and extended according to some cost function, which should be carefully selected to compensate for paths...
Game and Information Theory Analysis of Electronic Counter Measures in Pursuit-Evasion Games
Griffin, Christopher H [ORNL
2008-01-01
Two-player Pursuit-Evasion games in the literature typically either assume both players have perfect knowledge of the opponent s positions or use primitive sensing models. This unrealistically skews the problem in favor of the pursuer who need only maintain a faster velocity at all turning radii. In real life, an evader usually escapes when the pursuer no longer knows the evader s position. In our previous work, we modeled pursuit-evasion without perfect information as a two-player bi-matrix game by using a realistic sensor model and information theory to compute game theoretic payoff matrices. That game has a saddle point when the evader uses strategies that exploit sensor limitations, while the pursuer relies on strategies that ignore the sensing limitations. In this paper, we consider for the first time the effect of many types of electronic counter measures (ECM) on pursuit evasion games. The evader s decision to initiate its ECM is modeled as a function of the distance between the players. Simulations show how to find optimal strategies for ECM use when initial conditions are known. We also discuss the effectiveness of different ECM technologies in pursuit-evasion games.
34 CFR 370.45 - What limitation applies to the pursuit of legal remedies?
2010-07-01
... 34 Education 2 2010-07-01 2010-07-01 false What limitation applies to the pursuit of legal remedies? 370.45 Section 370.45 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF SPECIAL EDUCATION AND REHABILITATIVE SERVICES, DEPARTMENT OF EDUCATION CLIENT...
Shin, Jongho; Lee, Hyunjoo; McCarthy-Donovan, Alexander; Hwang, Hyeyoung; Yim, Sonyoung; Seo, EunJin
2015-01-01
The purpose of the study was to examine whether gender differences exist in the mean levels of and relations between adolescents' home environments (parents' view of science, socio-economic status (SES)), motivations (intrinsic and instrumental motivations, self-beliefs), and pursuit of science careers. For the purpose, the Programmed for…
Kong, Xiaoqing; Chakraverty, Devasmita; Jeffe, Donna B.; Andriole, Dorothy A.; Wathington, Heather D.; Tai, Robert H.
2013-01-01
This exploratory qualitative study investigated how doctoral students reported their personal and professional interaction experiences that they believed might facilitate or impede their academic pursuits in biomedical research. We collected 19 in-depth interviews with doctoral students in biomedical research from eight universities, and we based…
When goal pursuit fails: The functions of counterfactual thought in intention formation
Epstude, K.; Roese, N.J.
2011-01-01
Counterfactual thoughts predominantly occur in response to failed goal pursuit. The primary function of self-related counterfactuals seems to be correction of specific behaviors and preparation for future successful goal attainment. In the present article we describe a model that outlines this view
CONSERVATIVE ESTIMATING FUNCTIONIN THE NONLINEAR REGRESSION MODEL WITHAGGREGATED DATA
无
2000-01-01
The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.
Polynomial Regressions and Nonsense Inference
Daniel Ventosa-Santaulària
2013-11-01
Full Text Available Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples. In many cases, the data employed to estimate such specifications are time series that may exhibit stochastic nonstationary behavior. We extend Phillips’ results (Phillips, P. Understanding spurious regressions in econometrics. J. Econom. 1986, 33, 311–340. by proving that an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our results, therefore, lead to a call to be cautious whenever practitioners estimate polynomial regressions.
Producing The New Regressive Left
Crone, Christine
to be a committed artist, and how that translates into supporting al-Assad’s rule in Syria; the Ramadan programme Harrir Aqlak’s attempt to relaunch an intellectual renaissance and to promote religious pluralism; and finally, al-Mayadeen’s cooperation with the pan-Latin American TV station TeleSur and its ambitions...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...... coalition (Iran, Hizbollah, Syria), capitalises on a series of factors that bring them together in spite of their otherwise diverse worldviews and agendas. The New Regressive Left is united by resistance against the growing influence of Saudi Arabia in the religious, cultural, political, economic...
Heteroscedasticity checks for regression models
ZHU; Lixing
2001-01-01
［1］Carroll, R. J., Ruppert, D., Transformation and Weighting in Regression, New York: Chapman and Hall, 1988.［2］Cook, R. D., Weisberg, S., Diagnostics for heteroscedasticity in regression, Biometrika, 1988, 70: 1—10.［3］Davidian, M., Carroll, R. J., Variance function estimation, J. Amer. Statist. Assoc., 1987, 82: 1079—1091.［4］Bickel, P., Using residuals robustly I: Tests for heteroscedasticity, Ann. Statist., 1978, 6: 266—291.［5］Carroll, R. J., Ruppert, D., On robust tests for heteroscedasticity, Ann. Statist., 1981, 9: 205—209.［6］Eubank, R. L., Thomas, W., Detecting heteroscedasticity in nonparametric regression, J. Roy. Statist. Soc., Ser. B, 1993, 55: 145—155.［7］Diblasi, A., Bowman, A., Testing for constant variance in a linear model, Statist. and Probab. Letters, 1997, 33: 95—103.［8］Dette, H., Munk, A., Testing heteoscedasticity in nonparametric regression, J. R. Statist. Soc. B, 1998, 60: 693—708.［9］Müller, H. G., Zhao, P. L., On a semi-parametric variance function model and a test for heteroscedasticity, Ann. Statist., 1995, 23: 946—967.［10］Stute, W., Manteiga, G., Quindimil, M. P., Bootstrap approximations in model checks for regression, J. Amer. Statist. Asso., 1998, 93: 141—149.［11］Stute, W., Thies, G., Zhu, L. X., Model checks for regression: An innovation approach, Ann. Statist., 1998, 26: 1916—1939.［12］Shorack, G. R., Wellner, J. A., Empirical Processes with Applications to Statistics, New York: Wiley, 1986.［13］Efron, B., Bootstrap methods: Another look at the jackknife, Ann. Statist., 1979, 7: 1—26.［14］Wu, C. F. J., Jackknife, bootstrap and other re-sampling methods in regression analysis, Ann. Statist., 1986, 14: 1261—1295.［15］H rdle, W., Mammen, E., Comparing non-parametric versus parametric regression fits, Ann. Statist., 1993, 21: 1926—1947.［16］Liu, R. Y., Bootstrap procedures under some non-i.i.d. models, Ann. Statist., 1988, 16: 1696—1708.［17
Clustered regression with unknown clusters
Barman, Kishor
2011-01-01
We consider a collection of prediction experiments, which are clustered in the sense that groups of experiments ex- hibit similar relationship between the predictor and response variables. The experiment clusters as well as the regres- sion relationships are unknown. The regression relation- ships define the experiment clusters, and in general, the predictor and response variables may not exhibit any clus- tering. We call this prediction problem clustered regres- sion with unknown clusters (CRUC) and in this paper we focus on linear regression. We study and compare several methods for CRUC, demonstrate their applicability to the Yahoo Learning-to-rank Challenge (YLRC) dataset, and in- vestigate an associated mathematical model. CRUC is at the crossroads of many prior works and we study several prediction algorithms with diverse origins: an adaptation of the expectation-maximization algorithm, an approach in- spired by K-means clustering, the singular value threshold- ing approach to matrix rank minimization u...
Robust nonlinear regression in applications
Lim, Changwon; Sen, Pranab K.; Peddada, Shyamal D.
2013-01-01
Robust statistical methods, such as M-estimators, are needed for nonlinear regression models because of the presence of outliers/influential observations and heteroscedasticity. Outliers and influential observations are commonly observed in many applications, especially in toxicology and agricultural experiments. For example, dose response studies, which are routinely conducted in toxicology and agriculture, sometimes result in potential outliers, especially in the high dose gr...
Astronomical Methods for Nonparametric Regression
Steinhardt, Charles L.; Jermyn, Adam
2017-01-01
I will discuss commonly used techniques for nonparametric regression in astronomy. We find that several of them, particularly running averages and running medians, are generically biased, asymmetric between dependent and independent variables, and perform poorly in recovering the underlying function, even when errors are present only in one variable. We then examine less-commonly used techniques such as Multivariate Adaptive Regressive Splines and Boosted Trees and find them superior in bias, asymmetry, and variance both theoretically and in practice under a wide range of numerical benchmarks. In this context the chief advantage of the common techniques is runtime, which even for large datasets is now measured in microseconds compared with milliseconds for the more statistically robust techniques. This points to a tradeoff between bias, variance, and computational resources which in recent years has shifted heavily in favor of the more advanced methods, primarily driven by Moore's Law. Along these lines, we also propose a new algorithm which has better overall statistical properties than all techniques examined thus far, at the cost of significantly worse runtime, in addition to providing guidance on choosing the nonparametric regression technique most suitable to any specific problem. We then examine the more general problem of errors in both variables and provide a new algorithm which performs well in most cases and lacks the clear asymmetry of existing non-parametric methods, which fail to account for errors in both variables.
Estimates on compressed neural networks regression.
Zhang, Yongquan; Li, Youmei; Sun, Jianyong; Ji, Jiabing
2015-03-01
When the neural element number n of neural networks is larger than the sample size m, the overfitting problem arises since there are more parameters than actual data (more variable than constraints). In order to overcome the overfitting problem, we propose to reduce the number of neural elements by using compressed projection A which does not need to satisfy the condition of Restricted Isometric Property (RIP). By applying probability inequalities and approximation properties of the feedforward neural networks (FNNs), we prove that solving the FNNs regression learning algorithm in the compressed domain instead of the original domain reduces the sample error at the price of an increased (but controlled) approximation error, where the covering number theory is used to estimate the excess error, and an upper bound of the excess error is given.
Genetics Home Reference: caudal regression syndrome
... Twitter Home Health Conditions caudal regression syndrome caudal regression syndrome Enable Javascript to view the expand/collapse ... Download PDF Open All Close All Description Caudal regression syndrome is a disorder that impairs the development ...
Shape regression for vertebra fracture quantification
Lund, Michael Tillge; de Bruijne, Marleen; Tanko, Laszlo B.; Nielsen, Mads
2005-04-01
Accurate and reliable identification and quantification of vertebral fractures constitute a challenge both in clinical trials and in diagnosis of osteoporosis. Various efforts have been made to develop reliable, objective, and reproducible methods for assessing vertebral fractures, but at present there is no consensus concerning a universally accepted diagnostic definition of vertebral fractures. In this project we want to investigate whether or not it is possible to accurately reconstruct the shape of a normal vertebra, using a neighbouring vertebra as prior information. The reconstructed shape can then be used to develop a novel vertebra fracture measure, by comparing the segmented vertebra shape with its reconstructed normal shape. The vertebrae in lateral x-rays of the lumbar spine were manually annotated by a medical expert. With this dataset we built a shape model, with equidistant point distribution between the four corner points. Based on the shape model, a multiple linear regression model of a normal vertebra shape was developed for each dataset using leave-one-out cross-validation. The reconstructed shape was calculated for each dataset using these regression models. The average prediction error for the annotated shape was on average 3%.
Learning a Nonnegative Sparse Graph for Linear Regression.
Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung
2015-09-01
Previous graph-based semisupervised learning (G-SSL) methods have the following drawbacks: 1) they usually predefine the graph structure and then use it to perform label prediction, which cannot guarantee an overall optimum and 2) they only focus on the label prediction or the graph structure construction but are not competent in handling new samples. To this end, a novel nonnegative sparse graph (NNSG) learning method was first proposed. Then, both the label prediction and projection learning were integrated into linear regression. Finally, the linear regression and graph structure learning were unified within the same framework to overcome these two drawbacks. Therefore, a novel method, named learning a NNSG for linear regression was presented, in which the linear regression and graph learning were simultaneously performed to guarantee an overall optimum. In the learning process, the label information can be accurately propagated via the graph structure so that the linear regression can learn a discriminative projection to better fit sample labels and accurately classify new samples. An effective algorithm was designed to solve the corresponding optimization problem with fast convergence. Furthermore, NNSG provides a unified perceptiveness for a number of graph-based learning methods and linear regression methods. The experimental results showed that NNSG can obtain very high classification accuracy and greatly outperforms conventional G-SSL methods, especially some conventional graph construction methods.
The Analysis of the Regression-Discontinuity Design in R
Thoemmes, Felix; Liao, Wang; Jin, Ze
2017-01-01
This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…
李文新; 潘雄; 罗帆
2011-01-01
In order to optimize equipment function index and determine the goal engineering index under uncertain and fuzzy condition. Combine HoQ of quality function development (QFD) with fuzzy regression theory. Analyze QFD, HoQ model of military project development and the waterfall-like decomposition of military's need by QFD. At last, they are applied on some military project development to improve equipments' quality.%为在不确定的,模糊条件下优化产品的功能指标,确定工程特性目标值,将QFD质量屋与模糊回归理论相结合.分析QFD、军品项目开发中的质量屋模型以及QFD中军方顾客需求的瀑布式分解过程,简要论述模糊回归理论,最后将其应用于某国有企业军品项目开发中,能有效提高产品质量.
High regression rate, high density hybrid fuels Project
National Aeronautics and Space Administration — This SBIR program will investigate high energy density novel nanofuels combined with high density binders for use with an N2O oxidizer. Terves has developed...
On Weighted Support Vector Regression
Han, Xixuan; Clemmensen, Line Katrine Harder
2014-01-01
We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...
Multiatlas segmentation as nonparametric regression.
Awate, Suyash P; Whitaker, Ross T
2014-09-01
This paper proposes a novel theoretical framework to model and analyze the statistical characteristics of a wide range of segmentation methods that incorporate a database of label maps or atlases; such methods are termed as label fusion or multiatlas segmentation. We model these multiatlas segmentation problems as nonparametric regression problems in the high-dimensional space of image patches. We analyze the nonparametric estimator's convergence behavior that characterizes expected segmentation error as a function of the size of the multiatlas database. We show that this error has an analytic form involving several parameters that are fundamental to the specific segmentation problem (determined by the chosen anatomical structure, imaging modality, registration algorithm, and label-fusion algorithm). We describe how to estimate these parameters and show that several human anatomical structures exhibit the trends modeled analytically. We use these parameter estimates to optimize the regression estimator. We show that the expected error for large database sizes is well predicted by models learned on small databases. Thus, a few expert segmentations can help predict the database sizes required to keep the expected error below a specified tolerance level. Such cost-benefit analysis is crucial for deploying clinical multiatlas segmentation systems.
Software Effort Estimation with Ridge Regression and Evolutionary Attribute Selection
Papatheocharous, Efi; Andreou, Andreas S
2010-01-01
Software cost estimation is one of the prerequisite managerial activities carried out at the software development initiation stages and also repeated throughout the whole software life-cycle so that amendments to the total cost are made. In software cost estimation typically, a selection of project attributes is employed to produce effort estimations of the expected human resources to deliver a software product. However, choosing the appropriate project cost drivers in each case requires a lot of experience and knowledge on behalf of the project manager which can only be obtained through years of software engineering practice. A number of studies indicate that popular methods applied in the literature for software cost estimation, such as linear regression, are not robust enough and do not yield accurate predictions. Recently the dual variables Ridge Regression (RR) technique has been used for effort estimation yielding promising results. In this work we show that results may be further improved if an AI meth...
In pursuit of balance: Why your career path is unique
Rosenbloom, N. A.; Phillips, A. S.; Hannay, C.
2012-12-01
When NASA's Curiosity rover landed on Mars in August 2012, the room at JPL erupted in applause. Among the onlookers were highly trained scientists, engineers, programmers, and technicians with a wide range of career paths. The individuals remain anonymous, but each had a key role in the success of the mission. Behind every successful scientific project are the individuals who support the mission with their knowledge, commitment and curiosity. Whether by preference, personality, or ambition, many highly trained and qualified scientists choose to support science from behind-the-scenes. For these scientists, a supporting role in research remains a satisfying career choice. Other scientists attempt to race up the position ladder, eagerly taking leadership and/or more public roles. How do you decide which role is right for you, and how do you find balance in your chosen career path?
In pursuit of rigour and accountability in participatory design☆
Frauenberger, Christopher; Good, Judith; Fitzpatrick, Geraldine; Iversen, Ole Sejer
2015-01-01
The field of Participatory Design (PD) has greatly diversified and we see a broad spectrum of approaches and methodologies emerging. However, to foster its role in designing future interactive technologies, a discussion about accountability and rigour across this spectrum is needed. Rejecting the traditional, positivistic framework, we take inspiration from related fields such as Design Research and Action Research to develop interpretations of these concepts that are rooted in PD׳s own belief system. We argue that unlike in other fields, accountability and rigour are nuanced concepts that are delivered through debate, critique and reflection. A key prerequisite for having such debates is the availability of a language that allows designers, researchers and practitioners to construct solid arguments about the appropriateness of their stances, choices and judgements. To this end, we propose a “tool-to-think-with” that provides such a language by guiding designers, researchers and practitioners through a process of systematic reflection and critical analysis. The tool proposes four lenses to critically reflect on the nature of a PD effort: epistemology, values, stakeholders and outcomes. In a subsequent step, the coherence between the revealed features is analysed and shows whether they pull the project in the same direction or work against each other. Regardless of the flavour of PD, we argue that this coherence of features indicates the level of internal rigour of PD work and that the process of reflection and analysis provides the language to argue for it. We envision our tool to be useful at all stages of PD work: in the planning phase, as part of a reflective practice during the work, and as a means to construct knowledge and advance the field after the fact. We ground our theoretical discussions in a specific PD experience, the ECHOES project, to motivate the tool and to illustrate its workings. PMID:26109833
In pursuit of rigour and accountability in participatory design.
Frauenberger, Christopher; Good, Judith; Fitzpatrick, Geraldine; Iversen, Ole Sejer
2015-02-01
The field of Participatory Design (PD) has greatly diversified and we see a broad spectrum of approaches and methodologies emerging. However, to foster its role in designing future interactive technologies, a discussion about accountability and rigour across this spectrum is needed. Rejecting the traditional, positivistic framework, we take inspiration from related fields such as Design Research and Action Research to develop interpretations of these concepts that are rooted in PD׳s own belief system. We argue that unlike in other fields, accountability and rigour are nuanced concepts that are delivered through debate, critique and reflection. A key prerequisite for having such debates is the availability of a language that allows designers, researchers and practitioners to construct solid arguments about the appropriateness of their stances, choices and judgements. To this end, we propose a "tool-to-think-with" that provides such a language by guiding designers, researchers and practitioners through a process of systematic reflection and critical analysis. The tool proposes four lenses to critically reflect on the nature of a PD effort: epistemology, values, stakeholders and outcomes. In a subsequent step, the coherence between the revealed features is analysed and shows whether they pull the project in the same direction or work against each other. Regardless of the flavour of PD, we argue that this coherence of features indicates the level of internal rigour of PD work and that the process of reflection and analysis provides the language to argue for it. We envision our tool to be useful at all stages of PD work: in the planning phase, as part of a reflective practice during the work, and as a means to construct knowledge and advance the field after the fact. We ground our theoretical discussions in a specific PD experience, the ECHOES project, to motivate the tool and to illustrate its workings.
Bioucas-Dias, José M
2010-01-01
Convex optimization problems are common in hyperspectral unmixing. Examples are the constrained least squares (CLS) problem used to compute the fractional abundances in a linear mixture of known spectra, the constrained basis pursuit (CBP) to find sparse (i.e., with a small number of terms) linear mixtures of spectra, selected from large libraries, and the constrained basis pursuit denoising (CBPDN), which is a generalization of BP to admit modeling errors. In this paper, we introduce two new algorithms to efficiently solve these optimization problems, based on the alternating direction method of multipliers, a method from the augmented Lagrangian family. The algorithms are termed SUnSAL (sparse unmixing by variable splitting and augmented Lagrangian) and C-SUnSAL (constrained SUnSAL). C-SUnSAL solves the CBP and CBPDN problems, while SUnSAL solves CLS as well as a more general version thereof, called constrained sparse regression} (CSR). C-SUnSAL and SUnSAL are shown to outperform off-the-shelf methods in te...
Prediction, Regression and Critical Realism
Næss, Petter
2004-01-01
This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed....... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...
Nonparametric Regression with Common Shocks
Eduardo A. Souza-Rodrigues
2016-09-01
Full Text Available This paper considers a nonparametric regression model for cross-sectional data in the presence of common shocks. Common shocks are allowed to be very general in nature; they do not need to be finite dimensional with a known (small number of factors. I investigate the properties of the Nadaraya-Watson kernel estimator and determine how general the common shocks can be while still obtaining meaningful kernel estimates. Restrictions on the common shocks are necessary because kernel estimators typically manipulate conditional densities, and conditional densities do not necessarily exist in the present case. By appealing to disintegration theory, I provide sufficient conditions for the existence of such conditional densities and show that the estimator converges in probability to the Kolmogorov conditional expectation given the sigma-field generated by the common shocks. I also establish the rate of convergence and the asymptotic distribution of the kernel estimator.
Practical Session: Multiple Linear Regression
Clausel, M.; Grégoire, G.
2014-12-01
Three exercises are proposed to illustrate the simple linear regression. In the first one investigates the influence of several factors on atmospheric pollution. It has been proposed by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr33.pdf) and is based on data coming from 20 cities of U.S. Exercise 2 is an introduction to model selection whereas Exercise 3 provides a first example of analysis of variance. Exercises 2 and 3 have been proposed by A. Dalalyan at ENPC (see Exercises 2 and 3 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_5.pdf).
Lumbar herniated disc: spontaneous regression
Yüksel, Kasım Zafer
2017-01-01
Background Low back pain is a frequent condition that results in substantial disability and causes admission of patients to neurosurgery clinics. To evaluate and present the therapeutic outcomes in lumbar disc hernia (LDH) patients treated by means of a conservative approach, consisting of bed rest and medical therapy. Methods This retrospective cohort was carried out in the neurosurgery departments of hospitals in Kahramanmaraş city and 23 patients diagnosed with LDH at the levels of L3−L4, L4−L5 or L5−S1 were enrolled. Results The average age was 38.4 ± 8.0 and the chief complaint was low back pain and sciatica radiating to one or both lower extremities. Conservative treatment was administered. Neurological examination findings, durations of treatment and intervals until symptomatic recovery were recorded. Laségue tests and neurosensory examination revealed that mild neurological deficits existed in 16 of our patients. Previously, 5 patients had received physiotherapy and 7 patients had been on medical treatment. The number of patients with LDH at the level of L3−L4, L4−L5, and L5−S1 were 1, 13, and 9, respectively. All patients reported that they had benefit from medical treatment and bed rest, and radiologic improvement was observed simultaneously on MRI scans. The average duration until symptomatic recovery and/or regression of LDH symptoms was 13.6 ± 5.4 months (range: 5−22). Conclusions It should be kept in mind that lumbar disc hernias could regress with medical treatment and rest without surgery, and there should be an awareness that these patients could recover radiologically. This condition must be taken into account during decision making for surgical intervention in LDH patients devoid of indications for emergent surgery. PMID:28119770
Credit Scoring Problem Based on Regression Analysis
Khassawneh, Bashar Suhil Jad Allah
2014-01-01
ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....
Mikulas Pstross
2017-07-01
Full Text Available This article presents a reflective exploration on the relationship between community building and lifelong learning. Using a reflective style, the authors propose that the fusion of community building principles with lifelong learning practice can positively transform educational practice. Seven positive pursuits are highlighted regarding their potential to assist the implementation of community building into a lifelong learning programs: (1 asset- based thinking; (2 critical reflection; (3 systems thinking; (4 cognitive vibrancy, (5 inclusiveness; (6 creative expression; and, (7 purpose in life. These pursuits draw upon the power of the community development field to bring about more positive transformative moments for individuals and communities participating in lifelong learning programs. The metaphor of bread making is used to illustrate how such transformative moments occur and why they are meaningful to individuals pursuing lifelong learning.
Mass enhances speed but diminishes turn capacity in terrestrial pursuit predators.
Wilson, Rory P; Griffiths, Iwan W; Mills, Michael G L; Carbone, Chris; Wilson, John W; Scantlebury, David M
2015-08-07
The dynamics of predator-prey pursuit appears complex, making the development of a framework explaining predator and prey strategies problematic. We develop a model for terrestrial, cursorial predators to examine how animal mass modulates predator and prey trajectories and affects best strategies for both parties. We incorporated the maximum speed-mass relationship with an explanation of why larger animals should have greater turn radii; the forces needed to turn scale linearly with mass whereas the maximum forces an animal can exert scale to a 2/3 power law. This clarifies why in a meta-analysis, we found a preponderance of predator/prey mass ratios that minimized the turn radii of predators compared to their prey. It also explained why acceleration data from wild cheetahs pursuing different prey showed different cornering behaviour with prey type. The outcome of predator prey pursuits thus depends critically on mass effects and the ability of animals to time turns precisely.
Culture, cognition and behavior in the pursuit of self-esteem
Strandell, Jacob
2016-01-01
Self-esteem research, arguably the largest field of research in the history of social science, has devoted much of its efforts to the idea that self-esteem causes a broad range of behavioral and social problems, but has failed to produce strong consistent evidence for most claims. However......, this research has conceptual and methodological problems, including a limited understanding of the role of culture, and the assumption that global levels of self-esteem are the main causal mechanism of interest. This paper argues that self-esteem motivated behavior may be better understood as socio......-culturally contextualized pursuits of valued identities, which are difficult to understand without considering their social and cultural conditions. Self-esteem is therefore at the intersection of culture and cognition, and it is argued that an interdisciplinary approach to self-esteem pursuits could be beneficial. A way...
Culture, cognition and behavior in the pursuit of self-esteem
Strandell, Jacob
2016-01-01
Self-esteem research, arguably the largest field of research in the history of social science, has devoted much of its efforts to the idea that self-esteem causes a broad range of behavioral and social problems, but has failed to produce strong consistent evidence for most claims. However......, this research has conceptual and methodological problems, including a limited understanding of the role of culture, and the assumption that global levels of self-esteem are the main causal mechanism of interest. This paper argues that self-esteem motivated behavior may be better understood as socio......-culturally contextualized pursuits of valued identities, which are difficult to understand without considering their social and cultural conditions. Self-esteem is therefore at the intersection of culture and cognition, and it is argued that an interdisciplinary approach to self-esteem pursuits could be beneficial. A way...
Effect of sex and joystick experience on pursuit tracking in adults.
Joseph, J E; Willingham, D B
2000-03-01
Using a joystick, adults (n = 39 males, 40 females in Experiment 1; n = 35 males, 40 females in Experiment 2; and n = 18 males, 18 females in Experiment 3) performed a computerized pursuit tracking task. Contrary to previously reported findings, the males were not more accurate than the females when performance was adjusted for prior perceptual-motor experience. Although no sex differences were found in a speeded tracking task, in an inverted tracking task the males exhibited a significant performance advantage; that advantage remained after several blocks of practice. Because participants' performance was adjusted statistically for prior perceptual-motor experience, the male advantage in inverted tracking was not related to experience. Rather, more proficient inverted tracking performance was associated with higher 3-dimensional mental rotations scores. In sum, sex differences in normal pursuit tracking may be better explained by differences in perceptual-motor experience. Inverted tracking, however, may depend on proficiency with spatial transformations.
Toward realistic pursuit-evasion using a roadmap-based approach
Rodriguez, Samuel
2011-05-01
In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. Our approach can be applied to more realistic scenarios than are typically studied in most previous work, including agents moving in 3D environments such as terrains, multi-story buildings, and dynamic environments. We also support more realistic three-dimensional visibility computations that allow evading agents to hide in crowds or behind hills. We demonstrate the utility of this approach on mobile robots and in simulation for a variety of scenarios including pursuit-evasion and tag on terrains, in multi-level buildings, and in crowds. © 2011 IEEE.
The pursuit flexibility of children with attention-deficit/hyperactive disorder
Chin-Liang Tsai
2010-12-01
Full Text Available This research explores the kinematics performance of children with ADHD on the Pursuit Test at four speeds (i.e., 30, 50, 80, 100 millimeters per second to assess their movement flexibility and its quality. The study consists of 23 children with ADHD and 38 normal children. The results have shown that children with ADHD demonstrate a faster speed in movement, along with greater acceleration, and the entire movement process tends to be less smooth. Children with ADHD also demonstrated greater difficulty in motor control while the speeds of pursuit test increased. Discussion regarding children with ADHD had difficulty in implementing close-loop movements, higher-level cognitive processing, and higher-speed activities were proposed. Clinical implications, study limitations and suggestions for future study were provided.
The pursuit flexibility of children with attention-deficit/hyperactive disorder
M-J Chen-Sea
2010-11-01
Full Text Available This research explores the kinematics performance of children with ADHD on the Pursuit Test at four speeds (i.e., 30, 50, 80, 100 millimeters per second to assess their movement flexibility and its quality. The study consists of 23 children with ADHD and 38 normal children. The results have shown that children with ADHD demonstrate a faster speed in movement, along with greater acceleration, and the entire movement process tends to be less smooth. Children with ADHD also demonstrated greater difficulty in motor control while the speeds of pursuit test increased. Discussion regarding children with ADHD had difficulty in implementing close-loop movements, higher-level cognitive processing, and higher-speed activities were proposed. Clinical implications, study limitations and suggestions for future study were provided.
Capa, Rémi; Cleeremans, Axel; Bustin, Gaëlle; Bouquet, Cedric A.; Hansenne, Michel
2011-01-01
Building on the work of Aarts and coworkers on nonconscious goal pursuit, the present studyinvestigates whether subliminal processes may motivate effortful behavior and perseverance to learn coursework. We exposed students to a priming task in which subliminal representation of the goal of studying was directly paired (priming-positive group) or not (priming group) to a positive word. There was also a control group without subliminal prime of the goal. Next, students performed a learning task...
Utility-value intervention with parents increases students’ STEM preparation and career pursuit
Rozek, Christopher S.; Svoboda, Ryan C.; Harackiewicz, Judith M.; Hulleman, Chris S.; Hyde, Janet S.
2017-01-01
During high school, developing competence in science, technology, engineering, and mathematics (STEM) is critically important as preparation to pursue STEM careers, yet students in the United States lag behind other countries, ranking 35th in mathematics and 27th in science achievement internationally. Given the importance of STEM careers as drivers of modern economies, this deficiency in preparation for STEM careers threatens the United States’ continued economic progress. In the present study, we evaluated the long-term effects of a theory-based intervention designed to help parents convey the importance of mathematics and science courses to their high-school–aged children. A prior report on this intervention showed that it promoted STEM course-taking in high school; in the current follow-up study, we found that the intervention improved mathematics and science standardized test scores on a college preparatory examination (ACT) for adolescents by 12 percentile points. Greater high-school STEM preparation (STEM course-taking and ACT scores) was associated with increased STEM career pursuit (i.e., STEM career interest, the number of college STEM courses, and students’ attitudes toward STEM) 5 y after the intervention. These results suggest that the intervention can affect STEM career pursuit indirectly by increasing high-school STEM preparation. This finding underscores the importance of targeting high-school STEM preparation to increase STEM career pursuit. Overall, these findings demonstrate that a motivational intervention with parents can have important effects on STEM preparation in high school, as well as downstream effects on STEM career pursuit 5 y later. PMID:28096393
Utility-value intervention with parents increases students' STEM preparation and career pursuit.
Rozek, Christopher S; Svoboda, Ryan C; Harackiewicz, Judith M; Hulleman, Chris S; Hyde, Janet S
2017-01-31
During high school, developing competence in science, technology, engineering, and mathematics (STEM) is critically important as preparation to pursue STEM careers, yet students in the United States lag behind other countries, ranking 35th in mathematics and 27th in science achievement internationally. Given the importance of STEM careers as drivers of modern economies, this deficiency in preparation for STEM careers threatens the United States' continued economic progress. In the present study, we evaluated the long-term effects of a theory-based intervention designed to help parents convey the importance of mathematics and science courses to their high-school-aged children. A prior report on this intervention showed that it promoted STEM course-taking in high school; in the current follow-up study, we found that the intervention improved mathematics and science standardized test scores on a college preparatory examination (ACT) for adolescents by 12 percentile points. Greater high-school STEM preparation (STEM course-taking and ACT scores) was associated with increased STEM career pursuit (i.e., STEM career interest, the number of college STEM courses, and students' attitudes toward STEM) 5 y after the intervention. These results suggest that the intervention can affect STEM career pursuit indirectly by increasing high-school STEM preparation. This finding underscores the importance of targeting high-school STEM preparation to increase STEM career pursuit. Overall, these findings demonstrate that a motivational intervention with parents can have important effects on STEM preparation in high school, as well as downstream effects on STEM career pursuit 5 y later.
A BRIEF TALK ON AMERICAN CULTURAL VALUES: REFLECTED ON THE MOVIE THE PURSUIT OF HAPPINESS
Temmy Temmy
2009-05-01
Full Text Available America as one of world’s biggest developed countries has a very strong influence on globaleconomy, politics, education, science, and military. America is also one of teaching Chinese as aforeign language destinations, therefore understanding American cultural values is very important.Article represents American cultural values based on a true story movie "The pursuit of Happiness".Research method applied was library research. It can be concluded that the characters, setting, andconflicts really presented the characteristics of American society.
2013-01-01
This exploratory qualitative study investigated how doctoral students reported their personal and professional interaction experiences that they believed might facilitate or impede their academic pursuits in biomedical research. We collected 19 in-depth interviews with doctoral students in biomedical research from eight universities, and we based our qualitative analytic approach on the work of Miles and Huberman. The results indicated that among different sources and types of interaction, ac...
2005-12-01
navigation autonome des Véhicules terrestres sans pilotes (UGV). Cet article résume l’état actuel de l’art de localiser des parcours avec la robotique ...continuait de fonctionner d’une manière stable et efficace. On peut en conclure que Pure Pursuit est utile à une grande variété d’applications robotiques
Wibault two-seat monoplane 8C2 : an all-metal pursuit and observation airplane
Serryer, J
1926-01-01
Michel Wibault's two seat monoplane 8C2, is similar to the Parasol pursuit monoplane which preceded it. It has no perishable parts in its structure and needs no special storage or coverings. The sample aeroplane uses a 500 HP Hispano-Suiza engine but can accept a 400-600HP engine from a variety of manufacturers with little difficulty. It uses a two blade tractor propeller.
Money and the Pursuit of Happiness: In Good Times and Bad
Erika Rasure
2012-01-01
Money and the Pursuit of Happiness: In Good Times and Bad is a consumer’s introductory guide of personal reflection with money. The book’s author discusses how to develop a foundational relationship with one’s financial self in an effort to establish ongoing happiness and life satisfaction. The book can be an effective resource recommended by financial and mental health practitioners to clients. The book can help introduce or guide ongoing discussions about who an individual is in relati...
In Pursuit of Excellence: A Student Guide to Elite Sports Development
Michael Hill
2007-01-01
DESCRIPTION This book is about how it is possible to achieve the excellence in sport in modern times. PURPOSE To cover the past of competitive sport of today as well as discussing current issues in sport such as drugs. The comparison of elite sporting methods in leading sport countries is also included. AUDIENCE Students in the field and anybody interested in modern sports especially in the history of it. FEATURES A comprehensive introduction about the pursuit of excellence in sport, covering...
Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor
Baofu Fang; Lu Chen; Hao Wang; Shuanglu Dai; Qiubo Zhong
2014-01-01
Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots’ individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on em...
Pursuit tracking and higher levels of skill development in the human pilot
Hess, R. A.
1981-01-01
A model of the human pilot is offered for pursuit tracking tasks; the model encompasses an existing model for compensatory tracking. The central hypothesis in the development of this model states that those primary structural elements in the compensatory model responsible for the pilot's equalization capabilities remain intact in the pursuit model. In this latter case, effective low-frequency inversion of the controlled-element dynamics occurs by feeding-forward derived input rate through the equalization dynamics, with low-frequency phase droop minimized. The sharp reduction in low-frequency phase lag beyond that associated with the disappearance of phase droop is seen to accompany relatively low-gain feedback of vehicle output. The results of some recent motion cue research are discussed and interpreted in terms of the compensatory-pursuit display dichotomy. Tracking with input preview is discussed in a qualitative way. In terms of the model, preview is shown to demand no fundamental changes in structure or equalization and to allow the pilot to eliminate the effective time delays that accrue in the inversion of the controlled-element dynamics. Precognitive behavior is discussed, and a model that encompasses all the levels of skill development outlined in the successive organizations of perception theory is finally proposed.
Spatial contexts can inhibit a mislocalization of visual stimuli during smooth pursuit.
Noguchi, Yasuki; Shimojo, Shinsuke; Kakigi, Ryusuke; Hoshiyama, Minoru
2007-10-30
The position of a flash presented during pursuit is mislocalized in the direction of the pursuit. Although this has been explained by a temporal mismatch between the slow visual processing of flash and fast efferent signals on eye positions, here we show that spatial contexts also play an important role in determining the flash position. We put various continuously lit objects (walls) between veridical and to-be-mislocalized positions of flash. Consequently, these walls significantly reduced the mislocalization of flash, preventing the flash from being mislocalized beyond the wall (Experiment 1). When the wall was shortened or had a hole in its center, the shape of the mislocalized flash was vertically shortened as if cutoff or funneled by the wall (Experiment 2). The wall also induced color interactions; a red wall made a green flash appear yellowish if it was in the path of mislocalization (Experiment 3). Finally, those flash-wall interactions could be induced even when the walls were presented after the disappearance of flash (Experiment 4). These results indicate that various features (position, shape, and color) of flash during pursuit are determined with an integration window that is spatially and temporally broad, providing a new insight for generating mechanisms of eye-movement mislocalizations.
Bradley and Lacaille: Praxis as Passionate Pursuit of Exact Science
Wilson, C. A.
1997-12-01
From 1700 to 1800, astronomical observation and prediction improved in accuracy by an order of magnitude or more: by century's end astronomers could trust catalogued and predicted positions to within a few arcseconds. Crucial to this improvement were the discoveries of Bradley, which grew out of an endeavor of "normal science," the attempt to confirm with precision Robert Hooke's earlier supposed discovery of annual parallax in Gamma Draconis. On the theoretical side, Bradley's discoveries led to the quiet demise of two earlier doctrines, the Tychonic System and the Aristotelian and Cartesian doctrine of the instantaneous transmission of light. On the side of praxis, Bradley's discoveries meant that observational astronomy must be re-done from the ground up. In 1742 Nicolas-Louis Lacaille (1713-62), who had been admitted to the Paris Academie des Sciences only the year before, proposed to his astronomer colleagues that they take up this task as a cooperative enterprise. His proposal met with silence, but he undertook the project on his own, making it his life's work. By 1757 he had completed his Fundamenta Astronomiae, including a catalogue of 400 bright stars in which for the first time star positions were corrected for aberration and nutation. In 1758 he published his solar tables, the first to incorporate lunar and planetary perturbations as well as aberration and nutation. Lacaille's pendulum clock was not temperature-compensated, and his sextant poorly calibrated, but he was to some extent able to compensate for these flaws by bringing a massive number of observations to bear. Till the 1790s his Fundamenta Astronomiae and Tabulae Solares were important for the increments in accuracy they brought about, and for the inspiration they gave to later astronomers such as Delambre.
Varying-coefficient functional linear regression
Wu, Yichao; Müller, Hans-Georg; 10.3150/09-BEJ231
2011-01-01
Functional linear regression analysis aims to model regression relations which include a functional predictor. The analog of the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a regression parameter function in one or two arguments. If, in addition, one has scalar predictors, as is often the case in applications to longitudinal studies, the question arises how to incorporate these into a functional regression model. We study a varying-coefficient approach where the scalar covariates are modeled as additional arguments of the regression parameter function. This extension of the functional linear regression model is analogous to the extension of conventional linear regression models to varying-coefficient models and shares its advantages, such as increased flexibility; however, the details of this extension are more challenging in the functional case. Our methodology combines smoothing methods with regularization by truncation at a finite numb...
Functional Regression for Quasar Spectra
Ciollaro, Mattia; Freeman, Peter; Genovese, Christopher; Lei, Jing; O'Connell, Ross; Wasserman, Larry
2014-01-01
The Lyman-alpha forest is a portion of the observed light spectrum of distant galactic nuclei which allows us to probe remote regions of the Universe that are otherwise inaccessible. The observed Lyman-alpha forest of a quasar light spectrum can be modeled as a noisy realization of a smooth curve that is affected by a `damping effect' which occurs whenever the light emitted by the quasar travels through regions of the Universe with higher matter concentration. To decode the information conveyed by the Lyman-alpha forest about the matter distribution, we must be able to separate the smooth `continuum' from the noise and the contribution of the damping effect in the quasar light spectra. To predict the continuum in the Lyman-alpha forest, we use a nonparametric functional regression model in which both the response and the predictor variable (the smooth part of the damping-free portion of the spectrum) are function-valued random variables. We demonstrate that the proposed method accurately predicts the unobserv...
Knowledge and Awareness: Linear Regression
Monika Raghuvanshi
2016-12-01
Full Text Available Knowledge and awareness are factors guiding development of an individual. These may seem simple and practicable, but in reality a proper combination of these is a complex task. Economically driven state of development in younger generations is an impediment to the correct manner of development. As youths are at the learning phase, they can be molded to follow a correct lifestyle. Awareness and knowledge are important components of any formal or informal environmental education. The purpose of this study is to evaluate the relationship of these components among students of secondary/ senior secondary schools who have undergone a formal study of environment in their curricula. A suitable instrument is developed in order to measure the elements of Awareness and Knowledge among the participants of the study. Data was collected from various secondary and senior secondary school students in the age group 14 to 20 years using cluster sampling technique from the city of Bikaner, India. Linear regression analysis was performed using IBM SPSS 23 statistical tool. There exists a weak relation between knowledge and awareness about environmental issues, caused due to routine practices mishandling; hence one component can be complemented by other for improvement in both. Knowledge and awareness are crucial factors and can provide huge opportunities in any field. Resource utilization for economic solutions may pave the way for eco-friendly products and practices. If green practices are inculcated at the learning phase, they may become normal routine. This will also help in repletion of the environment.
Streamflow forecasting using functional regression
Masselot, Pierre; Dabo-Niang, Sophie; Chebana, Fateh; Ouarda, Taha B. M. J.
2016-07-01
Streamflow, as a natural phenomenon, is continuous in time and so are the meteorological variables which influence its variability. In practice, it can be of interest to forecast the whole flow curve instead of points (daily or hourly). To this end, this paper introduces the functional linear models and adapts it to hydrological forecasting. More precisely, functional linear models are regression models based on curves instead of single values. They allow to consider the whole process instead of a limited number of time points or features. We apply these models to analyse the flow volume and the whole streamflow curve during a given period by using precipitations curves. The functional model is shown to lead to encouraging results. The potential of functional linear models to detect special features that would have been hard to see otherwise is pointed out. The functional model is also compared to the artificial neural network approach and the advantages and disadvantages of both models are discussed. Finally, future research directions involving the functional model in hydrology are presented.
向宗灿
2015-01-01
本文针对以X公司预算编制存在的问题，提出了解决方案。依据X公司近五年的财务数据，通过建立多元一次回归模型，选择最相关的研发费用因素来准确的预测出X公司2014年度研发费用总额。%Aiming at the problems in the budgeting of X company, this article puts forward the solutions. According to the financial data of X company in the nearly five years, a multivariate linear regression model is established to select the most relevant R&D factors to accurately predict the annual R&D total costs of X company in 2014.
Developments in Pursuit of a Micro-Optic Gyroscope
VAWTER, GREGORY A.; ZUBRZYCKI, WALTER J.; PEAKE, GREGORY M.; ALFORD, CHARLES; HARGETT, TERRY; SALTERS, BETTY; HUDGENS, JAMES J.; KINNEY, RAGON D.
2003-03-01
Rotation sensors (gyros) and accelerometers are essential components for all precision-guided weapons and autonomous mobile surveillance platforms. MEMS gyro development has been based primarily on the properties of moving mass to sense rotation and has failed to keep pace with the concurrent development of MEMS accelerometers because the reduction of size and therefore mass is substantially more detrimental to the performance of gyros than to accelerometers. A small ({approx}0.2 cu in), robust ({approx}20,000g), inexpensive ({approx}$500), tactical grade performance ({approx}10-20 deg/hr.) gyro is vital for the successful implementation of the next generation of ''smart'' weapons and surveillance apparatus. The range of applications (relevant to Sandia's mission) that are substantially enhanced in capability or enabled by the availability of a gyro possessing the above attributes includes nuclear weapon guidance, fuzing, and safing; synthetic aperture radar (SAR) motion compensation; autonomous air and ground vehicles; gun-launched munitions; satellite control; and personnel tracking. For example, a gyro of this capability would open for consideration more fuzing options for earth-penetration weapons. The MEMS gyros currently available are lacking in one or more of the aforementioned attributes. An integrated optical gyro, however, possesses the potential of achieving all desired attributes. Optical gyros use the properties of light to sense rotation and require no moving mass. Only the individual optical elements required for the generation, detection, and control of light are susceptible to shock. Integrating these elements immensely enhances the gyro's robustness while achieving size and cost reduction. This project's goal, a joint effort between organizations 2300 and 1700, was to demonstrate an RMOG produced from a monolithic photonic integrated circuit coupled with a SiON waveguide resonator. During this LDRD program, we
Principal component regression analysis with SPSS.
Liu, R X; Kuang, J; Gong, Q; Hou, X L
2003-06-01
The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.
Mukherjee, Trishna; Liu, Bing; Simoncini, Claudio; Osborne, Leslie C
2017-02-08
Despite the enduring interest in motion integration, a direct measure of the space-time filter that the brain imposes on a visual scene has been elusive. This is perhaps because of the challenge of estimating a 3D function from perceptual reports in psychophysical tasks. We take a different approach. We exploit the close connection between visual motion estimates and smooth pursuit eye movements to measure stimulus-response correlations across space and time, computing the linear space-time filter for global motion direction in humans and monkeys. Although derived from eye movements, we find that the filter predicts perceptual motion estimates quite well. To distinguish visual from motor contributions to the temporal duration of the pursuit motion filter, we recorded single-unit responses in the monkey middle temporal cortical area (MT). We find that pursuit response delays are consistent with the distribution of cortical neuron latencies and that temporal motion integration for pursuit is consistent with a short integration MT subpopulation. Remarkably, the visual system appears to preferentially weight motion signals across a narrow range of foveal eccentricities rather than uniformly over the whole visual field, with a transiently enhanced contribution from locations along the direction of motion. We find that the visual system is most sensitive to motion falling at approximately one-third the radius of the stimulus aperture. Hypothesizing that the visual drive for pursuit is related to the filtered motion energy in a motion stimulus, we compare measured and predicted eye acceleration across several other target forms.SIGNIFICANCE STATEMENT A compact model of the spatial and temporal processing underlying global motion perception has been elusive. We used visually driven smooth eye movements to find the 3D space-time function that best predicts both eye movements and perception of translating dot patterns. We found that the visual system does not appear to use
Spontaneous Regression of an Incidental Spinal Meningioma
Yilmaz, Ali; Kizilay, Zahir; Sair, Ahmet; Avcil, Mucahit; Ozkul, Ayca
2015-01-01
AIM: The regression of meningioma has been reported in literature before. In spite of the fact that the regression may be involved by hemorrhage, calcification or some drugs withdrawal, it is rarely observed spontaneously. CASE REPORT...
Common pitfalls in statistical analysis: Logistic regression.
Ranganathan, Priya; Pramesh, C S; Aggarwal, Rakesh
2017-01-01
Logistic regression analysis is a statistical technique to evaluate the relationship between various predictor variables (either categorical or continuous) and an outcome which is binary (dichotomous). In this article, we discuss logistic regression analysis and the limitations of this technique.
2D/3D Image Registration using Regression Learning.
Chou, Chen-Rui; Frederick, Brandon; Mageras, Gig; Chang, Sha; Pizer, Stephen
2013-09-01
In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object's 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region's motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method's application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof.
Semiparametric regression during 2003–2007
Ruppert, David
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
Unbalanced Regressions and the Predictive Equation
Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo
Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...
Nonparametric instrumental regression with non-convex constraints
Grasmair, M.; Scherzer, O.; Vanhems, A.
2013-03-01
This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.
Standards for Standardized Logistic Regression Coefficients
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Synthesizing Regression Results: A Factored Likelihood Method
Wu, Meng-Jia; Becker, Betsy Jane
2013-01-01
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…
Regression Analysis by Example. 5th Edition
Chatterjee, Samprit; Hadi, Ali S.
2012-01-01
Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…
Regression with Sparse Approximations of Data
Noorzad, Pardis; Sturm, Bob L.
2012-01-01
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected by...
Standards for Standardized Logistic Regression Coefficients
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Regression with Sparse Approximations of Data
Noorzad, Pardis; Sturm, Bob L.
2012-01-01
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...
Assumptions of Multiple Regression: Correcting Two Misconceptions
Matt N. Williams
2013-09-01
Full Text Available In 2002, an article entitled - Four assumptions of multiple regression that researchers should always test- by.Osborne and Waters was published in PARE. This article has gone on to be viewed more than 275,000 times.(as of August 2013, and it is one of the first results displayed in a Google search for - regression.assumptions- . While Osborne and Waters' efforts in raising awareness of the need to check assumptions.when using regression are laudable, we note that the original article contained at least two fairly important.misconceptions about the assumptions of multiple regression: Firstly, that multiple regression requires the.assumption of normally distributed variables; and secondly, that measurement errors necessarily cause.underestimation of simple regression coefficients. In this article, we clarify that multiple regression models.estimated using ordinary least squares require the assumption of normally distributed errors in order for.trustworthy inferences, at least in small samples, but not the assumption of normally distributed response or.predictor variables. Secondly, we point out that regression coefficients in simple regression models will be.biased (toward zero estimates of the relationships between variables of interest when measurement error is.uncorrelated across those variables, but that when correlated measurement error is present, regression.coefficients may be either upwardly or downwardly biased. We conclude with a brief corrected summary of.the assumptions of multiple regression when using ordinary least squares.
Functional linear regression via canonical analysis
He, Guozhong; Wang, Jane-Ling; Yang, Wenjing; 10.3150/09-BEJ228
2011-01-01
We study regression models for the situation where both dependent and independent variables are square-integrable stochastic processes. Questions concerning the definition and existence of the corresponding functional linear regression models and some basic properties are explored for this situation. We derive a representation of the regression parameter function in terms of the canonical components of the processes involved. This representation establishes a connection between functional regression and functional canonical analysis and suggests alternative approaches for the implementation of functional linear regression analysis. A specific procedure for the estimation of the regression parameter function using canonical expansions is proposed and compared with an established functional principal component regression approach. As an example of an application, we present an analysis of mortality data for cohorts of medflies, obtained in experimental studies of aging and longevity.
Robust Nonlinear Regression: A Greedy Approach Employing Kernels With Application to Image Denoising
Papageorgiou, George; Bouboulis, Pantelis; Theodoridis, Sergios
2017-08-01
We consider the task of robust non-linear regression in the presence of both inlier noise and outliers. Assuming that the unknown non-linear function belongs to a Reproducing Kernel Hilbert Space (RKHS), our goal is to estimate the set of the associated unknown parameters. Due to the presence of outliers, common techniques such as the Kernel Ridge Regression (KRR) or the Support Vector Regression (SVR) turn out to be inadequate. Instead, we employ sparse modeling arguments to explicitly model and estimate the outliers, adopting a greedy approach. The proposed robust scheme, i.e., Kernel Greedy Algorithm for Robust Denoising (KGARD), is inspired by the classical Orthogonal Matching Pursuit (OMP) algorithm. Specifically, the proposed method alternates between a KRR task and an OMP-like selection step. Theoretical results concerning the identification of the outliers are provided. Moreover, KGARD is compared against other cutting edge methods, where its performance is evaluated via a set of experiments with various types of noise. Finally, the proposed robust estimation framework is applied to the task of image denoising, and its enhanced performance in the presence of outliers is demonstrated.
Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.
Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo
2015-08-01
Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.
Regression in children with autism spectrum disorders.
Malhi, Prahbhjot; Singhi, Pratibha
2012-10-01
To understand the characteristics of autistic regression and to compare the clinical and developmental profile of children with autism spectrum disorders (ASD) in whom parents report developmental regression with age matched ASD children in whom no regression is reported. Participants were 35 (Mean age = 3.57 y, SD = 1.09) children with ASD in whom parents reported developmental regression before age 3 y and a group of age and IQ matched 35 ASD children in whom parents did not report regression. All children were recruited from the outpatient Child Psychology Clinic of the Department of Pediatrics of a tertiary care teaching hospital in North India. Multi-disciplinary evaluations including neurological, diagnostic, cognitive, and behavioral assessments were done. Parents were asked in detail about the age at onset of regression, type of regression, milestones lost, and event, if any, related to the regression. In addition, the Childhood Autism Rating Scale (CARS) was administered to assess symptom severity. The mean age at regression was 22.43 mo (SD = 6.57) and large majority (66.7%) of the parents reported regression between 12 and 24 mo. Most (75%) of the parents of the regression-autistic group reported regression in the language domain, particularly in the expressive language sector, usually between 18 and 24 mo of age. Regression of language was not an isolated phenomenon and regression in other domains was also reported including social skills (75%), cognition (31.25%). In majority of the cases (75%) the regression reported was slow and subtle. There were no significant differences in the motor, social, self help, and communication functioning between the two groups as measured by the DP II.There were also no significant differences between the two groups on the total CARS score and total number of DSM IV symptoms endorsed. However, the regressed children had significantly (t = 2.36, P = .021) more social deficits as per the DSM IV as
Automation of Flight Software Regression Testing
Tashakkor, Scott B.
2016-01-01
NASA is developing the Space Launch System (SLS) to be a heavy lift launch vehicle supporting human and scientific exploration beyond earth orbit. SLS will have a common core stage, an upper stage, and different permutations of boosters and fairings to perform various crewed or cargo missions. Marshall Space Flight Center (MSFC) is writing the Flight Software (FSW) that will operate the SLS launch vehicle. The FSW is developed in an incremental manner based on "Agile" software techniques. As the FSW is incrementally developed, testing the functionality of the code needs to be performed continually to ensure that the integrity of the software is maintained. Manually testing the functionality on an ever-growing set of requirements and features is not an efficient solution and therefore needs to be done automatically to ensure testing is comprehensive. To support test automation, a framework for a regression test harness has been developed and used on SLS FSW. The test harness provides a modular design approach that can compile or read in the required information specified by the developer of the test. The modularity provides independence between groups of tests and the ability to add and remove tests without disturbing others. This provides the SLS FSW team a time saving feature that is essential to meeting SLS Program technical and programmatic requirements. During development of SLS FSW, this technique has proved to be a useful tool to ensure all requirements have been tested, and that desired functionality is maintained, as changes occur. It also provides a mechanism for developers to check functionality of the code that they have developed. With this system, automation of regression testing is accomplished through a scheduling tool and/or commit hooks. Key advantages of this test harness capability includes execution support for multiple independent test cases, the ability for developers to specify precisely what they are testing and how, the ability to add
Laplacian embedded regression for scalable manifold regularization.
Chen, Lin; Tsang, Ivor W; Xu, Dong
2012-06-01
Semi-supervised learning (SSL), as a powerful tool to learn from a limited number of labeled data and a large number of unlabeled data, has been attracting increasing attention in the machine learning community. In particular, the manifold regularization framework has laid solid theoretical foundations for a large family of SSL algorithms, such as Laplacian support vector machine (LapSVM) and Laplacian regularized least squares (LapRLS). However, most of these algorithms are limited to small scale problems due to the high computational cost of the matrix inversion operation involved in the optimization problem. In this paper, we propose a novel framework called Laplacian embedded regression by introducing an intermediate decision variable into the manifold regularization framework. By using ∈-insensitive loss, we obtain the Laplacian embedded support vector regression (LapESVR) algorithm, which inherits the sparse solution from SVR. Also, we derive Laplacian embedded RLS (LapERLS) corresponding to RLS under the proposed framework. Both LapESVR and LapERLS possess a simpler form of a transformed kernel, which is the summation of the original kernel and a graph kernel that captures the manifold structure. The benefits of the transformed kernel are two-fold: (1) we can deal with the original kernel matrix and the graph Laplacian matrix in the graph kernel separately and (2) if the graph Laplacian matrix is sparse, we only need to perform the inverse operation for a sparse matrix, which is much more efficient when compared with that for a dense one. Inspired by kernel principal component analysis, we further propose to project the introduced decision variable into a subspace spanned by a few eigenvectors of the graph Laplacian matrix in order to better reflect the data manifold, as well as accelerate the calculation of the graph kernel, allowing our methods to efficiently and effectively cope with large scale SSL problems. Extensive experiments on both toy and real
Coordinating with Humans by Adjustable-Autonomy for Multirobot Pursuit (CHAMP)
Dumond, Danielle; Ayers, Jeanine; Schurr, Nathan; Carlin, Alan; Burke, Dustin; Rousseau, Jeffrey
2012-06-01
One of the primary challenges facing the modern small-unit tactical team is the ability of the unit to safely and effectively search, explore, clear and hold urbanized terrain that includes buildings, streets, and subterranean dwellings. Buildings provide cover and concealment to an enemy and restrict the movement of forces while diminishing their ability to engage the adversary. The use of robots has significant potential to reduce the risk to tactical teams and dramatically force multiply the small unit's footprint. Despite advances in robotic mobility, sensing capabilities, and human-robot interaction, the use of robots in room clearing operations remains nascent. CHAMP is a software system in development that integrates with a team of robotic platforms to enable them to coordinate with a human operator performing a search and pursuit task. In this way, the human operator can either give control to the robots to search autonomously, or can retain control and direct the robots where needed. CHAMP's autonomy is built upon a combination of adversarial pursuit algorithms and dynamic function allocation strategies that maximize the team's resources. Multi-modal interaction with CHAMP is achieved using novel gesture-recognition based capabilities to reduce the need for heads-down tele-operation. The Champ Coordination Algorithm addresses dynamic and limited team sizes, generates a novel map of the area, and takes into account mission goals, user preferences and team roles. In this paper we show results from preliminary simulated experiments and find that the CHAMP system performs faster than traditional search and pursuit algorithms.
Goal Pursuit, Now and Later: Temporal Compatibility of Different versus Similar Means
Jordan Etkin; Ratner, Rebecca K.
2013-01-01
Compatibility between the degree of similarity among means to goal attainment and the anticipated timing of goal pursuit increases goal-directed motivation. Six studies demonstrate that consumers are more motivated and willing to pay for means to goal attainment in the near term when they plan to use a set of different (vs. similar) means. In contrast, consumers are more motivated and willing to pay for means to goal attainment in the long term when they plan to use similar (vs. different) me...
The Pursuit Behind the Escape——The Analysis of Harry Angstrom in Rabbit,Run
贾娜
2008-01-01
<正>The author John Updike illustrates the various contradictions between Middle-class American couples,the old and the young,the father and the son,the urban and the suburb,the rich and the poor,the soul and the body,peace and war,the God and the secular in his works.In 1960, Updike earned his fame through the publishing of Rabbit,Run and introduced one of his most unforgettable characters,the small town basketball star,Harry "Rabbit" Angstrom.This paper aims to explore Harry Angstrom’s pursuit behind his four "runs".
Model emulates human smooth pursuit system producing zero-latency target tracking.
Bahill, A T; McDonald, J D
1983-01-01
Humans can overcome the 150 ms time delay of the smooth pursuit eye movement system and track smoothly moving visual targets with zero-latency. Our target-selective adaptive control model can also overcome an inherent time delay and produce zero-latency tracking. No other model or man-made system can do this. Our model is physically realizable and physiologically realistic. The technique used in our model should be useful for analyzing other time-delay systems, such as man-machine systems and robots.
Existence of Hierarchies and Human's Pursuit of Top Hierarchy Lead to Power Law
Yu, Shuiyuan; Liu, Haitao
2016-01-01
The power law is ubiquitous in natural and social phenomena, and is considered as a universal relationship between the frequency and its rank for diverse social systems. However, a general model is still lacking to interpret why these seemingly unrelated systems share great similarity. Through a detailed analysis of natural language texts and simulation experiments based on the proposed 'Hierarchical Selection Model', we found that the existence of hierarchies and human's pursuit of top hierarchy lead to the power law. Further, the power law is a statistical and emergent performance of hierarchies, and it is the universality of hierarchies that contributes to the ubiquity of the power law.
Recovery of Block-Sparse Representations from Noisy Observations via Orthogonal Matching Pursuit
Fang, Jun
2011-01-01
We study the problem of recovering the sparsity pattern of block-sparse signals from noise-corrupted measurements. A simple, efficient recovery method, namely, a block-version of the orthogonal matching pursuit (OMP) method, is considered in this paper and its behavior for recovering the block-sparsity pattern is analyzed. We provide sufficient conditions under which the block-version of the OMP can successfully recover the block-sparse representations in the presence of noise. Our analysis reveals that exploiting block-sparsity can improve the recovery ability and lead to a guaranteed recovery for a higher sparsity level. Numerical results are presented to corroborate our theoretical claim.
Using Regression Mixture Analysis in Educational Research
Cody S. Ding
2006-11-01
Full Text Available Conventional regression analysis is typically used in educational research. Usually such an analysis implicitly assumes that a common set of regression parameter estimates captures the population characteristics represented in the sample. In some situations, however, this implicit assumption may not be realistic, and the sample may contain several subpopulations such as high math achievers and low math achievers. In these cases, conventional regression models may provide biased estimates since the parameter estimates are constrained to be the same across subpopulations. This paper advocates the applications of regression mixture models, also known as latent class regression analysis, in educational research. Regression mixture analysis is more flexible than conventional regression analysis in that latent classes in the data can be identified and regression parameter estimates can vary within each latent class. An illustration of regression mixture analysis is provided based on a dataset of authentic data. The strengths and limitations of the regression mixture models are discussed in the context of educational research.
Gates, Henry Louis, Jr.
1994-01-01
Proposes that English studies is not a privileged route to addressing and redressing social ills. Questions whether literary studies is now or has ever been a "serious" enterprise or whether those who engage in it are overly self-serious. (HB)
Regression modeling methods, theory, and computation with SAS
Panik, Michael
2009-01-01
Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,
Beta blockers & left ventricular hypertrophy regression.
George, Thomas; Ajit, Mullasari S; Abraham, Georgi
2010-01-01
Left ventricular hypertrophy (LVH) particularly in hypertensive patients is a strong predictor of adverse cardiovascular events. Identifying LVH not only helps in the prognostication but also in the choice of therapeutic drugs. The prevalence of LVH is age linked and has a direct correlation to the severity of hypertension. Adequate control of blood pressure, most importantly central aortic pressure and blocking the effects of cardiomyocyte stimulatory growth factors like Angiotensin II helps in regression of LVH. Among the various antihypertensives ACE-inhibitors and angiotensin receptor blockers are more potent than other drugs in regressing LVH. Beta blockers especially the newer cardio selective ones do still have a role in regressing LVH albeit a minor one. A meta-analysis of various studies on LVH regression shows many lacunae. There have been no consistent criteria for defining LVH and documenting LVH regression. This article reviews current evidence on the role of Beta Blockers in LVH regression.
Applied regression analysis a research tool
Pantula, Sastry; Dickey, David
1998-01-01
Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...
High-dimensional regression with unknown variance
Giraud, Christophe; Verzelen, Nicolas
2011-01-01
We review recent results for high-dimensional sparse linear regression in the practical case of unknown variance. Different sparsity settings are covered, including coordinate-sparsity, group-sparsity and variation-sparsity. The emphasize is put on non-asymptotic analyses and feasible procedures. In addition, a small numerical study compares the practical performance of three schemes for tuning the Lasso esti- mator and some references are collected for some more general models, including multivariate regression and nonparametric regression.
Regression calibration with heteroscedastic error variance.
Spiegelman, Donna; Logan, Roger; Grove, Douglas
2011-01-01
The problem of covariate measurement error with heteroscedastic measurement error variance is considered. Standard regression calibration assumes that the measurement error has a homoscedastic measurement error variance. An estimator is proposed to correct regression coefficients for covariate measurement error with heteroscedastic variance. Point and interval estimates are derived. Validation data containing the gold standard must be available. This estimator is a closed-form correction of the uncorrected primary regression coefficients, which may be of logistic or Cox proportional hazards model form, and is closely related to the version of regression calibration developed by Rosner et al. (1990). The primary regression model can include multiple covariates measured without error. The use of these estimators is illustrated in two data sets, one taken from occupational epidemiology (the ACE study) and one taken from nutritional epidemiology (the Nurses' Health Study). In both cases, although there was evidence of moderate heteroscedasticity, there was little difference in estimation or inference using this new procedure compared to standard regression calibration. It is shown theoretically that unless the relative risk is large or measurement error severe, standard regression calibration approximations will typically be adequate, even with moderate heteroscedasticity in the measurement error model variance. In a detailed simulation study, standard regression calibration performed either as well as or better than the new estimator. When the disease is rare and the errors normally distributed, or when measurement error is moderate, standard regression calibration remains the method of choice.
Enhanced piecewise regression based on deterministic annealing
ZHANG JiangShe; YANG YuQian; CHEN XiaoWen; ZHOU ChengHu
2008-01-01
Regression is one of the important problems in statistical learning theory. This paper proves the global convergence of the piecewise regression algorithm based on deterministic annealing and continuity of global minimum of free energy w.r.t temperature, and derives a new simplified formula to compute the initial critical temperature. A new enhanced piecewise regression algorithm by using "migration of prototypes" is proposed to eliminate "empty cell" in the annealing process. Numerical experiments on several benchmark datasets show that the new algo-rithm can remove redundancy and improve generalization of the piecewise regres-sion model.
Geodesic least squares regression on information manifolds
Verdoolaege, Geert, E-mail: geert.verdoolaege@ugent.be [Department of Applied Physics, Ghent University, Ghent, Belgium and Laboratory for Plasma Physics, Royal Military Academy, Brussels (Belgium)
2014-12-05
We present a novel regression method targeted at situations with significant uncertainty on both the dependent and independent variables or with non-Gaussian distribution models. Unlike the classic regression model, the conditional distribution of the response variable suggested by the data need not be the same as the modeled distribution. Instead they are matched by minimizing the Rao geodesic distance between them. This yields a more flexible regression method that is less constrained by the assumptions imposed through the regression model. As an example, we demonstrate the improved resistance of our method against some flawed model assumptions and we apply this to scaling laws in magnetic confinement fusion.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R(2)) indicates the importance of independent variables in the outcome.
Logistic Regression for Evolving Data Streams Classification
YIN Zhi-wu; HUANG Shang-teng; XUE Gui-rong
2007-01-01
Logistic regression is a fast classifier and can achieve higher accuracy on small training data. Moreover,it can work on both discrete and continuous attributes with nonlinear patterns. Based on these properties of logistic regression, this paper proposed an algorithm, called evolutionary logistical regression classifier (ELRClass), to solve the classification of evolving data streams. This algorithm applies logistic regression repeatedly to a sliding window of samples in order to update the existing classifier, to keep this classifier if its performance is deteriorated by the reason of bursting noise, or to construct a new classifier if a major concept drift is detected. The intensive experimental results demonstrate the effectiveness of this algorithm.
New ridge parameters for ridge regression
A.V. Dorugade
2014-04-01
Full Text Available Hoerl and Kennard (1970a introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation. In this article, a new method for estimating ridge parameters in both situations of ordinary ridge regression (ORR and generalized ridge regression (GRR is proposed. The simulation study evaluates the performance of the proposed estimator based on the mean squared error (MSE criterion and indicates that under certain conditions the proposed estimators perform well compared to OLS and other well-known estimators reviewed in this article.
Bulcock, J. W.
The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…
Gerist, Saleheh; Maheri, Mahmoud R.
2016-12-01
In order to solve structural damage detection problem, a multi-stage method using particle swarm optimization is presented. First, a new spars recovery method, named Basis Pursuit (BP), is utilized to preliminarily identify structural damage locations. The BP method solves a system of equations which relates the damage parameters to the structural modal responses using the sensitivity matrix. Then, the results of this stage are subsequently enhanced to the exact damage locations and extents using the PSO search engine. Finally, the search space is reduced by elimination of some low damage variables using micro search (MS) operator embedded in the PSO algorithm. To overcome the noise present in structural responses, a method known as Basis Pursuit De-Noising (BPDN) is also used. The efficiency of the proposed method is investigated by three numerical examples: a cantilever beam, a plane truss and a portal plane frame. The frequency response is used to detect damage in the examples. The simulation results demonstrate the accuracy and efficiency of the proposed method in detecting multiple damage cases and exhibit its robustness regarding noise and its advantages compared to other reported solution algorithms.
Hartman, Rhea; Blustein, Leona; Morel, Diane; Davis, Lisa
2014-08-15
To design and implement 2 pharmaceutical industry elective courses and assess their impact on students' selection of advanced pharmacy practice experiences (APPEs) and pursuit of pharmaceutical industry fellowships. Two 2-credit-hour elective courses that explored careers within the prescription and nonprescription pharmaceutical drug industries were offered for second- and third-year pharmacy students in a doctor of pharmacy (PharmD) degree program. The impact of the courses on pharmacy students' pursuit of a pharmaceutical industry fellowship was evaluated based on responses to annual graduating students' exit surveys. A greater percentage (17.9%) of students who had taken a pharmaceutical industry elective course pursued a pharmaceutical industry fellowship compared to all PharmD graduates (4.8%). Of the students who enrolled in pharmaceutical industry APPEs, 31% had taken 1 of the 2 elective courses. Exposure to a pharmaceutical industry elective course within a college or school of pharmacy curriculum may increase students' interest in pursuing pharmaceutical industry fellowships and enrolling in pharmaceutical industry APPEs.
Exploring factors affecting registered nurses' pursuit of postgraduate education in Australia.
Ng, Linda; Eley, Robert; Tuckett, Anthony
2016-12-01
The aim of this study was to explore the factors influencing registered nurses' pursuit of postgraduate education in specialty nursing practice in Australia. Despite the increased requirement for postgraduate education for advanced practice, little has been reported on the contributory factors involved in the decision to undertake further education. The Nurses' Attitudes Towards Postgraduate Education instrument was administered to 1632 registered nurses from the Nurses and Midwives e-Cohort Study across Australia, with a response rate of 35.9% (n = 568). Data reduction techniques using principal component analysis with varimax rotation were used. The analysis identified a three-factor solution for 14 items, accounting for 52.5% of the variance of the scale: "facilitators," "professional recognition," and "inhibiting factors." Facilitators of postgraduate education accounted for 28.5% of the variance, including: (i) improves knowledge; (ii) increases nurses' confidence in clinical decision-making; (iii) enhances nurses' careers; (iv) improves critical thinking; (v) improves nurses' clinical skill; and (vi) increased job satisfaction. This new instrument has potential clinical and research applications to support registered nurses' pursuit of postgraduate education. © 2016 John Wiley & Sons Australia, Ltd.
DelDonno, Sophie R; Weldon, Anne L; Crane, Natania A; Passarotti, Alessandra M; Pruitt, Patrick J; Gabriel, Laura B; Yau, Wendy; Meyers, Kortni K; Hsu, David T; Taylor, Stephen F; Heitzeg, Mary M; Herbener, Ellen; Shankman, Stewart A; Mickey, Brian J; Zubieta, Jon-Kar; Langenecker, Scott A
2015-11-30
Anhedonia, the diminished anticipation and pursuit of reward, is a core symptom of major depressive disorder (MDD). Trait behavioral activation (BA), as a proxy for anhedonia, and behavioral inhibition (BI) may moderate the relationship between MDD and reward-seeking. The present studies probed for reward learning deficits, potentially due to aberrant BA and/or BI, in active or remitted MDD individuals compared to healthy controls (HC). Active MDD (Study 1) and remitted MDD (Study 2) participants completed the modified monetary incentive delay task (mMIDT), a behavioral reward-seeking task whose response window parameters were individually titrated to theoretically elicit equivalent accuracy between groups. Participants completed the BI Scale and BA Reward-Responsiveness and Drive Scales. Despite individual titration, active MDD participants won significantly less money than HCs. Higher Reward-Responsiveness scores predicted more won; Drive and BI were not predictive. Remitted MDD participants' performance did not differ from controls', and trait BA and BI measures did not predict r-MDD performance. These results suggest that diminished reward-responsiveness may contribute to decreased motivation and reward pursuit during active MDD, but that reward learning is intact in remission. Understanding individual reward processing deficits in MDD may inform personalized intervention addressing anhedonia and motivation deficits in select MDD patients.
Reciprocal feedback between self-concept and goal pursuit in daily life.
Wong, Alexander E; Vallacher, Robin R
2017-07-21
We hypothesized that self-knowledge and goal perseverance are mutually reinforcing because of the roles of self-knowledge in directing goal pursuit, and of goal pursuit in structuring the self-concept. To test this hypothesis, we used a daily diary design with 97 college-aged participants for 40 days to assess whether daily self-concept clarity and grit predict one another's next-day levels. Data were analyzed using multilevel cross-lagged panel modeling. Results indicated that daily self-concept clarity and grit had positive and symmetric associations with each other across time, while controlling for their respective previous values. Similar crossed results were also found when testing the model using individual daily self-concept clarity and grit items. The results are the first to indicate the existence of reinforcing feedback loops between self-concept clarity and grit, such that fluctuations in the clarity of self-knowledge are associated with fluctuations in goal resolve, and vice versa. Discussion centers on the implications of these results for the functional link between mind and action and on the study's heuristic value for subsequent research. © 2017 Wiley Periodicals, Inc.
Pursuit eye-movements in curve driving differentiate between future path and tangent point models.
Otto Lappi
Full Text Available For nearly 20 years, looking at the tangent point on the road edge has been prominent in models of visual orientation in curve driving. It is the most common interpretation of the commonly observed pattern of car drivers looking through a bend, or at the apex of the curve. Indeed, in the visual science literature, visual orientation towards the inside of a bend has become known as "tangent point orientation". Yet, it remains to be empirically established whether it is the tangent point the drivers are looking at, or whether some other reference point on the road surface, or several reference points, are being targeted in addition to, or instead of, the tangent point. Recently discovered optokinetic pursuit eye-movements during curve driving can provide complementary evidence over and above traditional gaze-position measures. This paper presents the first detailed quantitative analysis of pursuit eye movements elicited by curvilinear optic flow in real driving. The data implicates the far zone beyond the tangent point as an important gaze target area during steady-state cornering. This is in line with the future path steering models, but difficult to reconcile with any pure tangent point steering model. We conclude that the tangent point steering models do not provide a general explanation of eye movement and steering during a curve driving sequence and cannot be considered uncritically as the default interpretation when the gaze position distribution is observed to be situated in the region of the curve apex.
Cyclist drag in team pursuit: influence of cyclist sequence, stature, and arm spacing.
Defraeye, Thijs; Blocken, Bert; Koninckx, Erwin; Hespel, Peter; Verboven, Pieter; Nicolai, Bart; Carmeliet, Jan
2014-01-01
In team pursuit, the drag of a group of cyclists riding in a pace line is dependent on several factors, such as anthropometric characteristics (stature) and position of each cyclist as well as the sequence in which they ride. To increase insight in drag reduction mechanisms, the aerodynamic drag of four cyclists riding in a pace line was investigated, using four different cyclists, and for four different sequences. In addition, each sequence was evaluated for two arm spacings. Instead of conventional field or wind tunnel experiments, a validated numerical approach (computational fluid dynamics) was used to evaluate cyclist drag, where the bicycles were not included in the model. The cyclist drag was clearly dependent on his position in the pace line, where second and subsequent positions experienced a drag reduction up to 40%, compared to an individual cyclist. Individual differences in stature and position on the bicycle led to an intercyclist variation of this drag reduction at a specific position in the sequence, but also to a variation of the total drag of the group for different sequences. A larger drag area for the group was found when riding with wider arm spacing. Such numerical studies on cyclists in a pace line are useful for determining the optimal cyclist sequence for team pursuit.
Shin, Jongho; Lee, Hyunjoo; McCarthy-Donovan, Alexander; Hwang, Hyeyoung; Yim, Sonyoung; Seo, EunJin
2015-06-01
The purpose of the study was to examine whether gender differences exist in the mean levels of and relations between adolescents' home environments (parents' view of science, socio-economic status (SES)), motivations (intrinsic and instrumental motivations, self-beliefs), and pursuit of science careers. For the purpose, the Programmed for International Student Assessment 2006 data of Korean 15-year-old students were analysed. The results of the study showed that girls had lower levels of science intrinsic and instrumental motivations, self-beliefs, and science-career pursuit (SCP) as well as their parents' values in science less than boys. Gender similarities, rather than gender differences, existed in patterns of causal relationship among home environments, motivations, and SCP. The results showed positive effects for parents' higher value in science and SES on motivations, SCP, and for intrinsic and instrumental motivations on SCP for girls and boys. These results provide implications for educational interventions to decrease gender differences in science motivations and SCP, and to decrease adolescents' gender stereotypes.
Culture shapes whether the pursuit of happiness predicts higher or lower well-being.
Ford, Brett Q; Dmitrieva, Julia O; Heller, Daniel; Chentsova-Dutton, Yulia; Grossmann, Igor; Tamir, Maya; Uchida, Yukiko; Koopmann-Holm, Birgit; Floerke, Victoria A; Uhrig, Meike; Bokhan, Tatiana; Mauss, Iris B
2015-12-01
Pursuing happiness can paradoxically impair well-being. Here, the authors propose the potential downsides to pursuing happiness may be specific to individualistic cultures. In collectivistic (vs. individualistic) cultures, pursuing happiness may be more successful because happiness is viewed--and thus pursued--in relatively socially engaged ways. In 4 geographical regions that vary in level of collectivism (United States, Germany, Russia, East Asia), we assessed participants' well-being, motivation to pursue happiness, and to what extent they pursued happiness in socially engaged ways. Motivation to pursue happiness predicted lower well-being in the United States, did not predict well-being in Germany, and predicted higher well-being in Russia and in East Asia. These cultural differences in the link between motivation to pursue happiness and well-being were explained by cultural differences in the socially engaged pursuit of happiness. These findings suggest that culture shapes whether the pursuit of happiness is linked with better or worse well-being, perhaps via how people pursue happiness. (c) 2015 APA, all rights reserved).
Higher-order principal component pursuit via tensor approximation and convex optimization
Sijia Cai; Ping Wang; Linhao Li; Chuhan Zhang
2014-01-01
Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit (PCP). This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit (HOPCP), since it is critical in multi-way data analysis. Unlike the convexification (nuclear norm) for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme: the augmented Lagrangian alternating di-rection method (ALADM) and its truncated higher-order singular value decomposition (ALADM-THOSVD) version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computational y intractable problems. Experimental re-sults on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.
IN PURSUIT OF EXCELLENCE: A STUDENT GUIDE TO ELITE SPORTS DEVELOPMENT
Michael Hill
2007-09-01
Full Text Available DESCRIPTION This book is about how it is possible to achieve the excellence in sport in modern times. PURPOSE To cover the past of competitive sport of today as well as discussing current issues in sport such as drugs. The comparison of elite sporting methods in leading sport countries is also included. AUDIENCE Students in the field and anybody interested in modern sports especially in the history of it. FEATURES A comprehensive introduction about the pursuit of excellence in sport, covering the key issues such as the history and tradition of sporting excellence; comparisons of elite high-performance sport programmes in Australia, the USA, East Germany and France; the historical, social, political and economic impacts of sporting excellence in the UK; current issues and debates, including drugs in sport; and the future for high-performance sport. ASSESSMENT Having a clear framework for understanding and exploring key issues, questions for discussion, websites and suggestions for further reading, "In Pursuit of Excellence" is a helpful source for students and for any person interested in sport and sport-relevant issues
Selin Aviyente
2010-01-01
Full Text Available Joint time-frequency representations offer a rich representation of event related potentials (ERPs that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely used matching pursuit (MP approach, with a Gabor dictionary, to principal components extracted from the time-frequency domain. The proposed PCA-Gabor decomposition is compared with other time-frequency data reduction methods such as the time-frequency PCA approach alone and standard matching pursuit methods using a Gabor dictionary for both simulated and biological data. The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.
A dedicated greedy pursuit algorithm for sparse spectral representation of music sound
Rebollo-Neira, Laura; Aggarwal, Gagan
2016-10-01
A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal, as a linear superposition of as few spectral components as possible. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the Fast Fourier Transform. The achieved sparsity is theoretically equivalent to that rendered by the Orthogonal Matching Pursuit method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard Orthogonal Matching Pursuit algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral models is illustrated by comparison with the traditional method, in the line of the Short Time Fourier Transform, involving only the corresponding orthonormal trigonometric basis.
Aviyente, Selin; Bernat, Edward M.; Malone, Stephen M.; Iacono, William G.
2010-12-01
Joint time-frequency representations offer a rich representation of event related potentials (ERPs) that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely used matching pursuit (MP) approach, with a Gabor dictionary, to principal components extracted from the time-frequency domain. The proposed PCA-Gabor decomposition is compared with other time-frequency data reduction methods such as the time-frequency PCA approach alone and standard matching pursuit methods using a Gabor dictionary for both simulated and biological data. The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.
Incremental Net Effects in Multiple Regression
Lipovetsky, Stan; Conklin, Michael
2005-01-01
A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…
Regression Analysis and the Sociological Imagination
De Maio, Fernando
2014-01-01
Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.
Dealing with Outliers: Robust, Resistant Regression
Glasser, Leslie
2007-01-01
Least-squares linear regression is the best of statistics and it is the worst of statistics. The reasons for this paradoxical claim, arising from possible inapplicability of the method and the excessive influence of "outliers", are discussed and substitute regression methods based on median selection, which is both robust and resistant, are…
Competing Risks Quantile Regression at Work
Dlugosz, Stephan; Lo, Simon M. S.; Wilke, Ralf
2017-01-01
Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use...
Implementing Variable Selection Techniques in Regression.
Thayer, Jerome D.
Variable selection techniques in stepwise regression analysis are discussed. In stepwise regression, variables are added or deleted from a model in sequence to produce a final "good" or "best" predictive model. Stepwise computer programs are discussed and four different variable selection strategies are described. These…
Regression Model With Elliptically Contoured Errors
Arashi, M; Tabatabaey, S M M
2012-01-01
For the regression model where the errors follow the elliptically contoured distribution (ECD), we consider the least squares (LS), restricted LS (RLS), preliminary test (PT), Stein-type shrinkage (S) and positive-rule shrinkage (PRS) estimators for the regression parameters. We compare the quadratic risks of the estimators to determine the relative dominance properties of the five estimators.
Regression Analysis and the Sociological Imagination
De Maio, Fernando
2014-01-01
Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.
A Simulation Investigation of Principal Component Regression.
Allen, David E.
Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…
Should metacognition be measured by logistic regression?
Rausch, Manuel; Zehetleitner, Michael
2017-03-01
Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.
Atherosclerotic plaque regression: fact or fiction?
Shanmugam, Nesan; Román-Rego, Ana; Ong, Peter; Kaski, Juan Carlos
2010-08-01
Coronary artery disease is the major cause of death in the western world. The formation and rapid progression of atheromatous plaques can lead to serious cardiovascular events in patients with atherosclerosis. The better understanding, in recent years, of the mechanisms leading to atheromatous plaque growth and disruption and the availability of powerful HMG CoA-reductase inhibitors (statins) has permitted the consideration of plaque regression as a realistic therapeutic goal. This article reviews the existing evidence underpinning current therapeutic strategies aimed at achieving atherosclerotic plaque regression. In this review we also discuss imaging modalities for the assessment of plaque regression, predictors of regression and whether plaque regression is associated with a survival benefit.
Pathological assessment of liver fibrosis regression
WANG Bingqiong
2017-03-01
Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.
Spatial orientation of optokinetic nystagmus and ocular pursuit during orbital space flight.
Moore, Steven T; Cohen, Bernard; Raphan, Theodore; Berthoz, Alain; Clément, Gilles
2005-01-01
On Earth, eye velocity of horizontal optokinetic nystagmus (OKN) orients to gravito-inertial acceleration (GIA), the sum of linear accelerations acting on the head and body. We determined whether adaptation to micro-gravity altered this orientation and whether ocular pursuit exhibited similar properties. Eye movements of four astronauts were recorded with three-dimensional video-oculography. Optokinetic stimuli were stripes moving horizontally, vertically, and obliquely at 30 degrees/s. Ocular pursuit was produced by a spot moving horizontally or vertically at 20 degrees/s. Subjects were either stationary or were centrifuged during OKN with 1 or 0.5 g of interaural or dorsoventral centripetal linear acceleration. Average eye position during OKN (the beating field) moved into the quick-phase direction by 10 degrees during lateral and upward field movement in all conditions. The beating field did not shift up during downward OKN on Earth, but there was a strong upward movement of the beating field (9 degrees) during downward OKN in the absence of gravity; this likely represents an adaptation to the lack of a vertical 1-g bias in-flight. The horizontal OKN velocity axis tilted 9 degrees in the roll plane toward the GIA during interaural centrifugation, both on Earth and in space. During oblique OKN, the velocity vector tilted towards the GIA in the roll plane when there was a disparity between the direction of stripe motion and the GIA, but not when the two were aligned. In contrast, dorsoventral acceleration tilted the horizontal OKN velocity vector 6 degrees in pitch away from the GIA. Roll tilts of the horizontal OKN velocity vector toward the GIA during interaural centrifugation are consistent with the orientation properties of velocity storage, but pitch tilts away from the GIA when centrifuged while supine are not. We speculate that visual suppression during OKN may have caused the velocity vector to tilt away from the GIA during dorsoventral centrifugation
Quantile regression applied to spectral distance decay
Rocchini, D.; Cade, B.S.
2008-01-01
Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.
Hypotheses testing for fuzzy robust regression parameters
Kula, Kamile Sanli [Ahi Evran University, Department of Mathematics, 40200 Kirsehir (Turkey)], E-mail: sanli2004@hotmail.com; Apaydin, Aysen [Ankara University, Department of Statistics, 06100 Ankara (Turkey)], E-mail: apaydin@science.ankara.edu.tr
2009-11-30
The classical least squares (LS) method is widely used in regression analysis because computing its estimate is easy and traditional. However, LS estimators are very sensitive to outliers and to other deviations from basic assumptions of normal theory [Huynh H. A comparison of four approaches to robust regression. Psychol Bull 1982;92:505-12; Stephenson D. 2000. Available from: (http://folk.uib.no/ngbnk/kurs/notes/node38.html); Xu R, Li C. Multidimensional least-squares fitting with a fuzzy model. Fuzzy Sets and Systems 2001;119:215-23.]. If there exists outliers in the data set, robust methods are preferred to estimate parameters values. We proposed a fuzzy robust regression method by using fuzzy numbers when x is crisp and Y is a triangular fuzzy number and in case of outliers in the data set, a weight matrix was defined by the membership function of the residuals. In the fuzzy robust regression, fuzzy sets and fuzzy regression analysis was used in ranking of residuals and in estimation of regression parameters, respectively [Sanli K, Apaydin A. Fuzzy robust regression analysis based on the ranking of fuzzy sets. Inernat. J. Uncertainty Fuzziness and Knowledge-Based Syst 2008;16:663-81.]. In this study, standard deviation estimations are obtained for the parameters by the defined weight matrix. Moreover, we propose another point of view in hypotheses testing for parameters.
Regression modeling of ground-water flow
Cooley, R.L.; Naff, R.L.
1985-01-01
Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)
Nagasawa, Y; Demura, S; Hamazaki, H
2010-09-01
This study examined age and sex differences of controlled force exertion measured by a computer-generated quasi-random target-pursuit system in 207 males and 249 females aged 15 to 86 years. The participants matched submaximal grip exertion of their dominant hand to changing demand values, appearing as a moving quasi-random waveform on the display of a personal computer. They performed the test three times with 1-min intervals (one trial was 40 sec). The total sum of the percent of differences between the demand value and the grip exertion value for 25 sec was used as an evaluation parameter. The errors in controlled force exertion tended to increase constantly with age in both sexes. Significant linear regressions were identified, but there was no significant difference in the rate of increase in both sexes. Analysis of variance showed nonsignificant sex differences among means, except for those in individuals older than 60 years; significant differences between means in the groups older than the 40 yr.-old age group and the 20-24 yr.-old group were found in both sexes. Controlled force exertion did not show a significant sex difference and decreased gradually with age in both sexes, but decreased remarkably after 40 years of age.
Project 2010 Project Management
Happy, Robert
2010-01-01
The ideal on-the-job reference guide for project managers who use Microsoft Project 2010. This must-have guide to using Microsoft Project 2010 is written from a real project manager's perspective and is packed with information you can use on the job. The book explores using Project 2010 during phases of project management, reveals best practices, and walks you through project flow from planning through tracking to closure. This valuable book follows the processes defined in the PMBOK Guide, Fourth Edition , and also provides exam prep for Microsoft's MCTS: Project 2010 certification.: Explains
Relative risk regression analysis of epidemiologic data.
Prentice, R L
1985-11-01
Relative risk regression methods are described. These methods provide a unified approach to a range of data analysis problems in environmental risk assessment and in the study of disease risk factors more generally. Relative risk regression methods are most readily viewed as an outgrowth of Cox's regression and life model. They can also be viewed as a regression generalization of more classical epidemiologic procedures, such as that due to Mantel and Haenszel. In the context of an epidemiologic cohort study, relative risk regression methods extend conventional survival data methods and binary response (e.g., logistic) regression models by taking explicit account of the time to disease occurrence while allowing arbitrary baseline disease rates, general censorship, and time-varying risk factors. This latter feature is particularly relevant to many environmental risk assessment problems wherein one wishes to relate disease rates at a particular point in time to aspects of a preceding risk factor history. Relative risk regression methods also adapt readily to time-matched case-control studies and to certain less standard designs. The uses of relative risk regression methods are illustrated and the state of development of these procedures is discussed. It is argued that asymptotic partial likelihood estimation techniques are now well developed in the important special case in which the disease rates of interest have interpretations as counting process intensity functions. Estimation of relative risks processes corresponding to disease rates falling outside this class has, however, received limited attention. The general area of relative risk regression model criticism has, as yet, not been thoroughly studied, though a number of statistical groups are studying such features as tests of fit, residuals, diagnostics and graphical procedures. Most such studies have been restricted to exponential form relative risks as have simulation studies of relative risk estimation
Variable and subset selection in PLS regression
Høskuldsson, Agnar
2001-01-01
The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...
Applied Regression Modeling A Business Approach
Pardoe, Iain
2012-01-01
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a
Regressive language in severe head injury.
Thomsen, I V; Skinhoj, E
1976-09-01
In a follow-up study of 50 patients with severe head injuries three patients had echolalia. One patient with initially global aphasia had echolalia for some weeks when he started talking. Another patient with severe diffuse brain damage, dementia, and emotional regression had echolalia. The dysfunction was considered a detour performance. In the third patient echolalia and palilalia were details in a total pattern of regression lasting for months. The patient, who had extensive frontal atrophy secondary to a very severe head trauma, presented an extreme state of regression returning to a foetal-body pattern and behaving like a baby.
Regression of altitude-produced cardiac hypertrophy.
Sizemore, D. A.; Mcintyre, T. W.; Van Liere, E. J.; Wilson , M. F.
1973-01-01
The rate of regression of cardiac hypertrophy with time has been determined in adult male albino rats. The hypertrophy was induced by intermittent exposure to simulated high altitude. The percentage hypertrophy was much greater (46%) in the right ventricle than in the left (16%). The regression could be adequately fitted to a single exponential function with a half-time of 6.73 plus or minus 0.71 days (90% CI). There was no significant difference in the rates of regression for the two ventricles.
Regression of altitude-produced cardiac hypertrophy.
Sizemore, D. A.; Mcintyre, T. W.; Van Liere, E. J.; Wilson , M. F.
1973-01-01
The rate of regression of cardiac hypertrophy with time has been determined in adult male albino rats. The hypertrophy was induced by intermittent exposure to simulated high altitude. The percentage hypertrophy was much greater (46%) in the right ventricle than in the left (16%). The regression could be adequately fitted to a single exponential function with a half-time of 6.73 plus or minus 0.71 days (90% CI). There was no significant difference in the rates of regression for the two ventricles.
Determination of riverbank erosion probability using Locally Weighted Logistic Regression
Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos
2015-04-01
erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.
Hong, Jin-Chul; Sun, Kyung Ho; Kim, Yoon Young
2005-08-01
The success of the guided-wave damage inspection technology depends not only on the generation and measurement of desired waveforms but also on the signal processing of the measured waves, but less attention has been paid to the latter. This research aims to develop an efficient signal processing technique especially suitable for the current guided-wave technology. To achieve this objective, the use of a two-stage matching pursuit approach based on the Gabor dictionary is proposed. Instead of truncated sine pulses commonly used in waveguide inspection, Gabor pulses, the modulated Gaussian pulses, are chosen as the elastic energy carrier to facilitate the matching pursuit algorithm. To extract meaningful waves out of noisy signals, a two-stage matching pursuit strategy is developed, which consists of the following: rough approximations with a set of predetermined parameters characterizing the Gabor pulse, and fine adjustments of the parameters by optimization. The parameters estimated from measured longitudinal elastic waves can be then directly used to assess not only the location but also the size of a crack in a rod. For the estimation of the crack size, in particular, Love's theory is incorporated in the matching pursuit analysis. Several experiments were conducted to verify the validity of the proposed approach in damage assessment.
van Tricht, M. J.; Nieman, D. H.; Bour, L. J.; Boeree, T.; Koelman, J. H. T. M.; de Haan, L.; Linszen, D. H.
2010-01-01
Abnormalities in eye tracking are consistently observed in schizophrenia patients and their relatives and have been proposed as an endophenotype of the disease. The aim of this study was to investigate the performance of patients at Ultra High Risk (UHR) for developing psychosis on a task of smooth pursuit eye movement (SPEM). Forty-six UHR…
Gender and the Dark Side of the Border in Laila Lalami’s Hope and other Dangerous Pursuits
Kareem Al-Jayikh Ali
2016-12-01
Full Text Available Starting from Arab-American women’s narratives, this study explores to what extent hegemonic history excludes and silences female Arab bodies and their relation to sexuality. It will also address the issue of present day migration, as reflected by Moroccan-American author Laila Lalami in her novel Hope and Other Dangerous Pursuits (2005.
Cerven, Christine
2013-01-01
Drawing on a case study of 60 low-income single mothers in California, I present a grounded account of the barriers and supports single mothers encounter in their pursuit of postsecondary education (PSE) and detail what the women themselves attributed to their success. I highlight the role both significant others (peers, family, friends) and…
In precision agriculture regression has been used widely to quality the relationship between soil attributes and other environmental variables. However, spatial correlation existing in soil samples usually makes the regression model suboptimal. In this study, a regression-kriging method was attemp...
Regression periods in infancy. A case study from Catalonia.
Sadurní Brugué, Marta; Rostán Sánchez, Carles
2002-01-01
Based on Rijt-Plooij and Plooij’s (1992) research on emergence of regression periods in the first two years of life, the presence of such periods in a group of 18 babies (10 boys and 8 girls, aged between 3 weeks and 14 months) from a Catalonian population was analyzed. The measurements were a questionnaire filled in by the infants’ mothers, a semi-structured weekly tape-recorded interview, and observations in their homes. The procedure and the instruments used in the project follow those pro...
Money and the Pursuit of Happiness: In Good Times and Bad
Erika Rasure
2012-01-01
Full Text Available Money and the Pursuit of Happiness: In Good Times and Bad is a consumer’s introductory guide of personal reflection with money. The book’s author discusses how to develop a foundational relationship with one’s financial self in an effort to establish ongoing happiness and life satisfaction. The book can be an effective resource recommended by financial and mental health practitioners to clients. The book can help introduce or guide ongoing discussions about who an individual is in relation to money. In addition, this book offers a variety of real-life examples and exercises for readers, providing an opportunity to gain insight into their financial personalities.
The pursuit of excellence is not optional in the voluntary sector, it is essential.
Dunn, B; Mathews, S
2001-01-01
This paper outlines the continuous improvement journey of a voluntary organisation. The significant level of organisational growth and improving quality of services described is clearly linked to the organisation's commitment to improvement. One of the approaches used in adopting a total quality culture was the EFQM model, specifically interpreted for the voluntary sector. Until recently such an approach would have been considered alien to the sector, not least because of its origins in the business community. This article contradicts this assumption. Issues addressed include how the improvement process is driven, the use of performance measurement, external verification and the difficulties in accessing sector appropriate benchmark data. It is suggested that the pursuit of excellence is no longer optional for the voluntary sector, it is essential.
The effects of self-criticism and self-oriented perfectionism on goal pursuit.
Powers, Theodore A; Koestner, Richard; Zuroff, David C; Milyavskaya, Marina; Gorin, Amy A
2011-07-01
Five separate studies examined the associations of self-criticism and self-oriented perfectionism with goal pursuit across a variety of domains. Although self-criticism has previously been shown to be related to diminished goal progress, a controversy remains regarding the potential association between aspects of "positive perfectionism," such as self-oriented perfectionism, and enhanced goal progress. The results of the five studies demonstrated a consistent pattern of negative association between self-criticism and goal progress. The results also showed a positive association between self-oriented perfectionism and goal progress when self-criticism was controlled. The important role of self-criticism for understanding the impact of perfectionistic concerns is highlighted by these results. Implications for the debate concerning the possible positive effects of perfectionistic strivings are also discussed.
Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors
Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck
2015-01-01
This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. PMID:25591168
Lieff, Susan J
2009-10-01
Retention of faculty in academic medicine is a growing challenge. It has been suggested that inattention to the humanistic values of the faculty is contributing to this problem. Professional development should consider faculty members' search for meaning, purpose, and professional fulfillment and should support the development of an ability to reflect on these issues. Ensuring the alignment of academic physicians' inner direction with their outer context is critical to professional fulfillment and effectiveness. Personal reflection on the synergy of one's strengths, passions, and values can help faculty members define meaningful work so as to enable clearer career decision making. The premise of this article is that an awareness of and the pursuit of meaningful work and its alignment with the academic context are important considerations in the professional fulfillment and retention of academic faculty. A conceptual framework for understanding meaningful work and alignment and ways in which that framework can be applied and taught in development programs are presented and discussed.
The pursuit of happiness measurement: a psychometric model based on psychophysiological correlates.
Pietro, Cipresso; Silvia, Serino; Giuseppe, Riva
2014-01-01
Everyone is interested in the pursuit of happiness, but the real problem for the researchers is how to measure it. Our aim was to deeply investigate happiness measurement through biomedical signals, using psychophysiological methods to objectify the happiness experiences measurements. The classic valence-arousal model of affective states to study happiness has been extensively used in psychophysiology. However, really few studies considered a real combination of these two dimensions and no study further investigated multidimensional models. More, most studies focused mainly on self-report to measure happiness and a deeper psychophysiological investigation on the dimensions of such an experience is still missing. A multidimensional model of happiness is presented and both the dimensions and the measures extracted within each dimension are comprehensively explained. This multidimensional model aims at being a milestone for future systematic study on psychophysiology of happiness and affective states.
Nested Multi- and Many-Objective Optimisation of Team Track Pursuit Cycling
Markus Wagner
2016-10-01
Full Text Available Team pursuit track cycling is an elite sport that is part of the Summer Olympics. Teams race against each other on special tracks called velodromes. In this article, we create racing strategies that allow the team to complete the race in as little time as possible. In addition to the traditional minimisation of the race times, we consider the amount of energy that the riders have left at the end of the race. For the team coach this extension can have the benefit that a diverse set of trade-off strategies can be considered. For the optimisation approach, the added diversity can help to get over local optima.To solve this problem, we apply different state-of-the-art algorithms with problem-specific variation operators. It turns out that nesting algorithms is beneficial for achieving fast strategies reliably.
Godfrey Baldacchino
2008-05-01
Full Text Available The pursuit of nissology, or island studies, calls for a re-centering of focus from mainland to island, away from the discourse of conquest of mainlanders, giving voice and platform for the expression of island narratives. Yet, studying islands ‘on their own terms’, in spite of its predilection for “authenticity”, is fraught with epistemological and methodological difficulties. The insider/outsider distinction does not work all that well when it comes to islands, where hybridity is the norm. This paper seeks to extend this debate, grappling especially with the contributions of Grant McCall and Peter Hay to the sparse literature. Five dilemmas related to indigenous island geographies are presented and discussed, in a semi-autobiographical style.
Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph
Yan Jing; Guan Xin-Ping; Luo Xiao-Yuan
2011-01-01
This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents, and agents will pursue the target once they detect its existence. Since the ability of each agent may be different, we consider the heterogeneous multi-agent systems.According to the topology of the multi-agent systems, a novel consensus-based control law is proposed, where the target and agents are modeled as a leader and followers, respectively. Based on Mason's rule and signal flow graph analysis, the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally, simulation studies are provided to verify the effectiveness of the proposed approach.
Simultaneous Greedy Analysis Pursuit for compressive sensing of multi-channel ECG signals.
Avonds, Yurrit; Liu, Yipeng; Van Huffel, Sabine
2014-01-01
This paper addresses compressive sensing for multi-channel ECG. Compared to the traditional sparse signal recovery approach which decomposes the signal into the product of a dictionary and a sparse vector, the recently developed cosparse approach exploits sparsity of the product of an analysis matrix and the original signal. We apply the cosparse Greedy Analysis Pursuit (GAP) algorithm for compressive sensing of ECG signals. Moreover, to reduce processing time, classical signal-channel GAP is generalized to the multi-channel GAP algorithm, which simultaneously reconstructs multiple signals with similar support. Numerical experiments show that the proposed method outperforms the classical sparse multi-channel greedy algorithms in terms of accuracy and the single-channel cosparse approach in terms of processing speed.
Structure Analysis of Network Traffic Matrix Based on Relaxed Principal Component Pursuit
Wang, Zhe; Xu, Ke; Yin, Baolin
2011-01-01
The network traffic matrix is a kind of flow-level Internet traffic data and is widely applied to network operation and management. It is a crucial problem to analyze the composition and structure of traffic matrix; some mathematical approaches such as Principal Component Analysis (PCA) were used to handle that problem. In this paper, we first argue that PCA performs poorly for analyzing traffic matrixes polluted by large volume anomalies, then propose a new composition model of the network traffic matrix. According to our model, structure analysis can be formally defined as decomposing a traffic matrix into low-rank, sparse, and noise sub-matrixes, which is equal to the Robust Principal Component Analysis (RPCA) problem defined in [13]. Based on the Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated Proximal Gradient (APG) algorithm, an iterative algorithm for decomposing a traffic matrix is presented, and our experiment results demonstrate its efficiency and flexibility. At last, f...
Head Pursuit Variable Structure Guidance Law for Three-dimensional Space Interception
Ge Lianzheng; Shen Yi; Gao Yunfeng; Zhao Lijun
2008-01-01
This article aims to develop a head pursuit (HP) guidance law for three-dimensional hypervelocity interception,so that the effect of the perturbation induced by seeker detection can be reduced.On the basis of a novel I-IP three-dimensional guidance model,a nonlinear variable structure guidance law is presented by using Lyapunov stability theory.The guidance law positions the interceptor ahead of the target on its flight trajectory,and the speed of the interceptor is required to be lower than that of the target.A numerical example of maneuvering ballistic target interception verifies the rightness of the guidance model and the effectiveness of the proposed method.
Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors
Jonathan Las Fargeas
2015-01-01
Full Text Available This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles’ paths nominally. The algorithm uses detections from the sensors to predict intruders’ locations and selects the vehicles’ paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm’s completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios.
Fsheikh, Ahmed H.
2013-01-01
A nonlinear orthogonal matching pursuit (NOMP) for sparse calibration of reservoir models is presented. Sparse calibration is a challenging problem as the unknowns are both the non-zero components of the solution and their associated weights. NOMP is a greedy algorithm that discovers at each iteration the most correlated components of the basis functions with the residual. The discovered basis (aka support) is augmented across the nonlinear iterations. Once the basis functions are selected from the dictionary, the solution is obtained by applying Tikhonov regularization. The proposed algorithm relies on approximate gradient estimation using an iterative stochastic ensemble method (ISEM). ISEM utilizes an ensemble of directional derivatives to efficiently approximate gradients. In the current study, the search space is parameterized using an overcomplete dictionary of basis functions built using the K-SVD algorithm.
Multiple Instance Regression with Structured Data
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
This slide presentation reviews the use of multiple instance regression with structured data from multiple and related data sets. It applies the concept to a practical problem, that of estimating crop yield using remote sensed country wide weekly observations.
Prediction of Dynamical Systems by Symbolic Regression
Quade, Markus; Shafi, Kamran; Niven, Robert K; Noack, Bernd R
2016-01-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting a...
Some Simple Computational Formulas for Multiple Regression
Aiken, Lewis R., Jr.
1974-01-01
Short-cut formulas are presented for direct computation of the beta weights, the standard errors of the beta weights, and the multiple correlation coefficient for multiple regression problems involving three independent variables and one dependent variable. (Author)
Spontaneous Regression of an Incidental Spinal Meningioma
Ali Yilmaz
2015-12-01
Full Text Available AIM: The regression of meningioma has been reported in literature before. In spite of the fact that the regression may be involved by hemorrhage, calcification or some drugs withdrawal, it is rarely observed spontaneously. CASE REPORT: We report a 17 year old man with a cervical meningioma which was incidentally detected. In his cervical MRI an extradural, cranio-caudal contrast enchanced lesion at C2-C3 levels of the cervical spinal cord was detected. Despite the slight compression towards the spinal cord, he had no symptoms and refused any kind of surgical approach. The meningioma was followed by control MRI and it spontaneously regressed within six months. There were no signs of hemorrhage or calcification. CONCLUSION: Although it is a rare condition, the clinicians should consider that meningiomas especially incidentally diagnosed may be regressed spontaneously.
Spontaneous Regression of an Incidental Spinal Meningioma.
Yilmaz, Ali; Kizilay, Zahir; Sair, Ahmet; Avcil, Mucahit; Ozkul, Ayca
2016-03-15
The regression of meningioma has been reported in literature before. In spite of the fact that the regression may be involved by hemorrhage, calcification or some drugs withdrawal, it is rarely observed spontaneously. We report a 17 year old man with a cervical meningioma which was incidentally detected. In his cervical MRI an extradural, cranio-caudal contrast enchanced lesion at C2-C3 levels of the cervical spinal cord was detected. Despite the slight compression towards the spinal cord, he had no symptoms and refused any kind of surgical approach. The meningioma was followed by control MRI and it spontaneously regressed within six months. There were no signs of hemorrhage or calcification. Although it is a rare condition, the clinicians should consider that meningiomas especially incidentally diagnosed may be regressed spontaneously.
Patterns of Regression in Rett Syndrome
J Gordon Millichap
2002-10-01
Full Text Available Patterns and features of regression in a case series of 53 girls and women with Rett syndrome were studied at the Institute of Child Health and Great Ormond Street Children’s Hospital, London, UK.
A new bivariate negative binomial regression model
Faroughi, Pouya; Ismail, Noriszura
2014-12-01
This paper introduces a new form of bivariate negative binomial (BNB-1) regression which can be fitted to bivariate and correlated count data with covariates. The BNB regression discussed in this study can be fitted to bivariate and overdispersed count data with positive, zero or negative correlations. The joint p.m.f. of the BNB1 distribution is derived from the product of two negative binomial marginals with a multiplicative factor parameter. Several testing methods were used to check overdispersion and goodness-of-fit of the model. Application of BNB-1 regression is illustrated on Malaysian motor insurance dataset. The results indicated that BNB-1 regression has better fit than bivariate Poisson and BNB-2 models with regards to Akaike information criterion.
Heteroscedastic regression analysis method for mixed data
FU Hui-min; YUE Xiao-rui
2011-01-01
The heteroscedastic regression model was established and the heteroscedastic regression analysis method was presented for mixed data composed of complete data, type- I censored data and type- Ⅱ censored data from the location-scale distribution. The best unbiased estimations of regression coefficients, as well as the confidence limits of the location parameter and scale parameter were given. Furthermore, the point estimations and confidence limits of percentiles were obtained. Thus, the traditional multiple regression analysis method which is only suitable to the complete data from normal distribution can be extended to the cases of heteroscedastic mixed data and the location-scale distribution. So the presented method has a broad range of promising applications.
Recovery of sparse translation-invariant signals with continuous basis pursuit.
Ekanadham, Chaitanya; Tranchina, Daniel; Simoncelli, Eero
2011-10-01
We consider the problem of decomposing a signal into a linear combination of features, each a continuously translated version of one of a small set of elementary features. Although these constituents are drawn from a continuous family, most current signal decomposition methods rely on a finite dictionary of discrete examples selected from this family (e.g., shifted copies of a set of basic waveforms), and apply sparse optimization methods to select and solve for the relevant coefficients. Here, we generate a dictionary that includes auxiliary interpolation functions that approximate translates of features via adjustment of their coefficients. We formulate a constrained convex optimization problem, in which the full set of dictionary coefficients represents a linear approximation of the signal, the auxiliary coefficients are constrained so as to only represent translated features, and sparsity is imposed on the primary coefficients using an L1 penalty. The basis pursuit denoising (BP) method may be seen as a special case, in which the auxiliary interpolation functions are omitted, and we thus refer to our methodology as continuous basis pursuit (CBP). We develop two implementations of CBP for a one-dimensional translation-invariant source, one using a first-order Taylor approximation, and another using a form of trigonometric spline. We examine the tradeoff between sparsity and signal reconstruction accuracy in these methods, demonstrating empirically that trigonometric CBP substantially outperforms Taylor CBP, which in turn offers substantial gains over ordinary BP. In addition, the CBP bases can generally achieve equally good or better approximations with much coarser sampling than BP, leading to a reduction in dictionary dimensionality.
Chiu, Hsiu-Ching; Halaki, Mark; O'Dwyer, Nicholas
2013-04-30
Most previous studies of associated reactions (ARs) in people with cerebral palsy have used observation scales, such as recording the degree of movement through observation. The sensitive quantitative method can detect ARs that are not amply visible. The aim of this study was to provide quantitative measures of ARs during a visual pursuit position tracking task. Twenty-three hemiplegia (H) (mean +/- SD: 21y 8m +/- 11y 10m), twelve quadriplegia (Q) (21y 5m +/- 10y 3m) and twenty-two subjects with normal development (N) (21y 2m +/- 10y 10m) participated in the study. An upper limb visual pursuit tracking task was used to study ARs. The participants were required to follow a moving target with a response cursor via elbow flexion and extension movements. The occurrence of ARs was quantified by the overall coherence between the movements of tracking and non-tracking limbs and the amount of movement due to ARs was quantified by the amplitude of movement the non-tracking limbs. The amplitude of movement of the non-tracking limb indicated that the amount of ARs was larger in the Q group than the H and N groups with no significant differences between the H and N groups. The amplitude of movement of the non-tracking limb was larger during non-dominant than dominant tracking in all three groups. Some movements in the non-tracking limb were correlated with the tracking limb (correlated ARs) and some movements that were not correlated with the tracking limb (uncorrelated ARs). The correlated ARs comprised less than 40% of the total ARs for all three groups. Correlated ARs were negatively associated with clinical evaluations, but not the uncorrelated ARs. The correlated and uncorrelated ARs appear to have different relationships with clinical evaluations, implying the effect of ARs on upper limb activities could be varied.
METHODOLOGY AND RESULTS OF MOBILE OBJECT PURSUIT PROBLEM SOLUTION WITH TWO-STAGE DYNAMIC SYSTEM
A. Kiselev Mikhail
2017-01-01
Full Text Available The experience of developing unmanned fighting vehicles indicates that the main challenge in this field reduces itself to creating the systems which can replace the pilot both as a sensor and as the operator of the flight. This problem can be partial- ly solved by introducing remote control, but there are certain flight segments where it can only be executed under fully inde- pendent control and data support due to various reasons, such as tight time, short duration, lack of robust communication, etc. Such stages also include close-range air combat maneuvering (CRACM - a key flight segment as far as the fighter's purpose is concerned, which also places the highest demands on the fighter's design. Until recently the creation of an unmanned fighter airplane has been a fundamentally impossible task due to the absence of sensors able to provide the necessary data support to control the fighter during CRACM. However, the development prospects of aircraft hardware (passive type flush antennae, op- tico-locating panoramic view stations are indicative of producing possible solutions to this problem in the nearest future. There- fore, presently the only fundamental impediment on the way to developing an unmanned fighting aircraft is the problem of cre- ating algorithms for automatic trajectory control during CRACM. This paper presents the strategy of automatic trajectory con- trol synthesis by a two-stage dynamic system aiming to reach the conditions specified with respect to an object in pursuit. It contains certain results of control algorithm parameters impact assessment in regards to the pursuit mission effectiveness. Based on the obtained results a deduction is drawn pertaining to the efficiency of the offered method and its possible utilization in au- tomated control of an unmanned fighting aerial vehicle as well as organizing group interaction during CRACM.
Recommendations for the successful pursuit of scholarship by pharmacy practice faculty members.
Bosso, John A; Hastings, Jan K; Speedie, Marilyn K; Rodriguez de Bittner, Magaly
2015-02-17
Scholarship has long been a basic expectation of faculty members at institutions of higher learning in the United States and elsewhere. This expectation is no less assumed in academic pharmacy. A number of organizations have verbalized and enforced this precept over the years.(1-3) For example, this expectation is spoken to directly in the American Council for Pharmacy Education's Accreditation Standards and Guidelines.(4) This expectation is further emphasized in the draft document of the accreditation standards to be implemented in 2016, in Standard 20. Specifically, Element 20.2 states: "The college or school must create an environment that both requires and promotes scholarship, and must also develop mechanisms to assess both the quantity and quality of faculty scholarly productivity."(5) The successful pursuit of scholarship by clinical faculty members (those engaged in both clinical practice and teaching, without regard to tenure or clinical track status) is challenging. (6-10) Thus, faculty member job descriptions or models should be designed so clinical faculty members can successfully meet all academic job expectations, including productive and meaningful scholarship. In 2012, an AACP Section of Teachers of Pharmacy Practice task force was charged with examining this issue and providing recommendations for models for clinical faculty members that would allow the successful pursuit of scholarship. The task force gathered information relating to the current state of affairs at a number of colleges and reviewed relevant literature. This information, along with personal experiences and much discussion and contemplation, led to some general observations as well as specific recommendations. This paper reiterates the task force's observations and recommendations and provides further detail regarding our interpretation of the findings and basis for the eventual recommendations to the section.
Lingli Cui
2014-09-01
Full Text Available This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and
Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui
2014-09-09
This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm
Superquantile Regression: Theory, Algorithms, and Applications
2014-12-01
Isabel. I love having you in my arms, and although you are still too young to understand what a hug is, your warmth has given me the strength and...squares and the quantile regression models adjust to changes in the data set, denoted by the red dots. Notice that the observa- tions are moved upwards...model hardly changes. If we change this observation in red even further upwards, we would notice no more changes in the quantile regression function
Marginal longitudinal semiparametric regression via penalized splines
Al Kadiri, M.
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Boosted regression tree, table, and figure data
Spreadsheets are included here to support the manuscript Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition. This dataset is associated with the following publication:Golden , H., C. Lane , A. Prues, and E. D'Amico. Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition. JAWRA. American Water Resources Association, Middleburg, VA, USA, 52(5): 1251-1274, (2016).
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Spontaneous regression of metastatic Merkel cell carcinoma.
Hassan, S J
2010-01-01
Merkel cell carcinoma is a rare aggressive neuroendocrine carcinoma of the skin predominantly affecting elderly Caucasians. It has a high rate of local recurrence and regional lymph node metastases. It is associated with a poor prognosis. Complete spontaneous regression of Merkel cell carcinoma has been reported but is a poorly understood phenomenon. Here we present a case of complete spontaneous regression of metastatic Merkel cell carcinoma demonstrating a markedly different pattern of events from those previously published.
The Infinite Hierarchical Factor Regression Model
Rai, Piyush
2009-01-01
We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.
Marginal longitudinal semiparametric regression via penalized splines.
Kadiri, M Al; Carroll, R J; Wand, M P
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Multiple-Instance Regression with Structured Data
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.
[Iris movement mediates pupillary membrane regression].
Morizane, Yuki
2007-11-01
In the course of mammalian lens development, a transient capillary meshwork called as the pupillary membrane (PM) forms. It is located in the pupil area to nourish the anterior surface of the lens, and then regresses to clear the optical path. Although the involvement of the apoptotic process has been reported in PM regression, the initiating factor remains unknown. We initially found that regression of the PM coincided with the development of iris motility, and that iris movement caused cessation and resumption of blood flow within the PM. Therefore, we investigated whether the development of the capacity of the iris to constrict and dilate can function as an essential signal that induces apoptosis in the PM. Continuous inhibition of iris movement with mydriatic agents suppressed apoptosis of the PM and resulted in the persistence of PM in rats. The distribution of apoptotic cells in the regressing PM was diffuse and showed no apparent localization. These results indicated that iris movement induced regression of the PM by changing the blood flow within it. This study suggests the importance of the physiological interactions between tissues-in this case, the iris and the PM-as a signal to advance vascular regression during organ development.
Post-processing through linear regression
B. Van Schaeybroeck
2011-03-01
Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.
These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
Post-processing through linear regression
van Schaeybroeck, B.; Vannitsem, S.
2011-03-01
Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
Adams, Rick A; Bauer, Markus; Pinotsis, Dimitris; Friston, Karl J
2016-05-15
This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories and the ERFs. The DCM for pursuit was based on predictive coding and active inference, and predicts subjects' eye movements based on their (subjective) Bayesian beliefs about target (and eye) motion. The precisions of these hierarchical beliefs can be inferred from behavioural (pursuit) data. The DCM for MEG data used an established biophysical model of neuronal activity that includes parameters for the gain of superficial pyramidal cells, which is thought to encode precision at the neuronal level. Previous studies (using DCM of pursuit data) suggest that noisy target motion increases subjective precision at the sensory level: i.e., subjects attend more to the target's sensory attributes. We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data. We demonstrate that imprecise target motion increases the gain of superficial pyramidal cells in V1 (across subjects). Furthermore, increases in sensory precision - inferred by our behavioural DCM - correlate with the increase in gain in V1, across subjects. This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia.